{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys, os\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import time \n",
    "\n",
    "# DWave Credentials\n",
    "dwave_solver = os.getenv('DWAVE_API_SOLVER')\n",
    "api_key = os.getenv('DWAVE_API_TOKEN')\n",
    "\n",
    "from dwave.system.samplers import DWaveSampler\n",
    "from dwave.system.composites import EmbeddingComposite\n",
    "\n",
    "import dwave_networkx as dnx\n",
    "import dimod\n",
    "\n",
    "samplerSA = dimod.SimulatedAnnealingSampler()\n",
    "\n",
    "import networkx as nx\n",
    "\n",
    "sampler = EmbeddingComposite(DWaveSampler(solver=dwave_solver, token=api_key))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset = 'sectors' # values: 'asset_class','ftse','sectors','sp100'\n",
    "\n",
    "corr_tensor = np.load('%s_corr.npy' % (dataset))\n",
    "dates = np.load('%s_dates.npy' % (dataset))\n",
    "nodes = np.load('%s_nodes.npy' % (dataset))\n",
    "nodes_descr = np.load('%s_nodes_descr.npy' % (dataset))\n",
    "\n",
    "num_examples = corr_tensor.shape[0] #number of dates\n",
    "dim = corr_tensor.shape[1] #number of assets\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Helper Functions\n",
    "\n",
    "def make_graph(corr_mat, node_labels, graph_type):\n",
    "\n",
    "    G = nx.Graph()\n",
    "    G.add_nodes_from(node_labels)\n",
    "    dim = corr_mat.shape[0]\n",
    "\n",
    "    if not dim == len(node_labels):\n",
    "        raise ValueError('number node labels not = corr matrix dimensions')\n",
    "\n",
    "    if graph_type=='signed':\n",
    "        for i in range(dim):\n",
    "            for j in range(i+1, dim):\n",
    "                if corr_mat[i,j] < 0:\n",
    "                    G.add_edge(node_labels[i], node_labels[j], sign=-1)\n",
    "                elif corr_mat[i,j] > 0:\n",
    "                    G.add_edge(node_labels[i], node_labels[j], sign=1)\n",
    "    \n",
    "    if graph_type=='corr':\n",
    "        for i in range(dim):\n",
    "            for j in range(i+1, dim):\n",
    "                if corr_mat[i,j] != 0.000:\n",
    "                    G.add_edge(node_labels[i], node_labels[j])\n",
    "    \n",
    "    if graph_type=='uncorr':\n",
    "        for i in range(dim):\n",
    "            for j in range(i+1, dim):\n",
    "                if corr_mat[i,j] == 0.000:\n",
    "                    G.add_edge(node_labels[i], node_labels[j])\n",
    "    \n",
    "    density = (2*G.number_of_edges())/(G.number_of_nodes()*(G.number_of_nodes() - 1))\n",
    "                \n",
    "    return G, density\n",
    "\n",
    "def get_max_deg(G):\n",
    "    degree_sequence = sorted([d for n, d in G.degree()], reverse=True)\n",
    "\n",
    "    return max(degree_sequence)\n",
    "\n",
    "def coloring_score(G, coloring):\n",
    "    count = 0\n",
    "    for e in G.edges():\n",
    "        v1, v2 = e\n",
    "        if coloring[v1] == coloring[v2]:\n",
    "            count += 1\n",
    "        \n",
    "        return count/G.number_of_edges()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# source code for DWave coloring algorithm - modified to include timing\n",
    "\n",
    "from __future__ import division\n",
    "\n",
    "import math\n",
    "import itertools\n",
    "\n",
    "import networkx as nx\n",
    "from dwave_networkx import _PY2\n",
    "from dwave_networkx.utils import binary_quadratic_model_sampler\n",
    "\n",
    "__all__ = [\"min_vertex_coloring\", \"is_vertex_coloring\", \"is_cycle\"]\n",
    "\n",
    "# compatibility for python 2/3\n",
    "if _PY2:\n",
    "    range = xrange\n",
    "\n",
    "    def iteritems(d): return d.iteritems()\n",
    "\n",
    "    def ceil(n): return int(math.ceil(n))\n",
    "else:\n",
    "    def iteritems(d): return d.items()\n",
    "    ceil = math.ceil\n",
    "\n",
    "try:\n",
    "    import numpy\n",
    "    eigenvalues = numpy.linalg.eigvals\n",
    "except ImportError:\n",
    "    eigenvalues = False\n",
    "\n",
    "\n",
    "\n",
    "@binary_quadratic_model_sampler(1)\n",
    "def min_vertex_coloring(G, sampler=None, **sampler_args):\n",
    "\n",
    "    # if the given graph is not connected, apply the function to each connected component\n",
    "    # seperately.\n",
    "    if not nx.is_connected(G):\n",
    "        coloring = {}\n",
    "        for subG in (G.subgraph(c).copy() for c in nx.connected_components(G)):\n",
    "            sub_coloring = min_vertex_coloring(subG, sampler, **sampler_args)\n",
    "            coloring.update(sub_coloring)\n",
    "        return coloring\n",
    "\n",
    "    n_nodes = len(G)  # number of nodes\n",
    "    n_edges = len(G.edges)  # number of edges\n",
    "\n",
    "    # ok, first up, we can eliminate a few graph types trivially\n",
    "\n",
    "    # Graphs with no edges, have chromatic number 1\n",
    "    if not n_edges:\n",
    "        return {node: 0 for node in G}\n",
    "\n",
    "    # Complete graphs have chromatic number N\n",
    "    if n_edges == n_nodes * (n_nodes - 1) // 2:\n",
    "        return {node: color for color, node in enumerate(G)}\n",
    "\n",
    "    # The number of variables in the QUBO is approximately the number of nodes in the graph\n",
    "    # times the number of potential colors, so we want as tight an upper bound on the\n",
    "    # chromatic number (chi) as possible\n",
    "    chi_ub = _chromatic_number_upper_bound(G, n_nodes, n_edges)\n",
    "\n",
    "    # now we can start coloring. Without loss of generality, we can determine some of\n",
    "    # the node colors before trying to solve.\n",
    "    partial_coloring, possible_colors, chi_lb = _partial_precolor(G, chi_ub)\n",
    "\n",
    "    # ok, to get the rest of the coloring, we need to start building the QUBO. We do this\n",
    "    # by assigning a variable x_v_c for each node v and color c. This variable will be 1\n",
    "    # when node v is colored c, and 0 otherwise.\n",
    "\n",
    "    # let's assign an index to each of the variables\n",
    "    counter = itertools.count()\n",
    "    x_vars = {v: {c: next(counter) for c in possible_colors[v]} for v in possible_colors}\n",
    "\n",
    "    # now we have three different constraints we wish to add.\n",
    "\n",
    "    # the first constraint enforces the coloring rule, that for each pair of vertices\n",
    "    # u, v that share an edge, they should be different colors\n",
    "    Q_neighbor = _vertex_different_colors_qubo(G, x_vars)\n",
    "\n",
    "    # the second constraint enforces that each vertex has a single color assigned\n",
    "    Q_vertex = _vertex_one_color_qubo(x_vars)\n",
    "\n",
    "    # the third constraint is that we want a minimum vertex coloring, so we want to\n",
    "    # disincentivize the colors we might not need.\n",
    "    Q_min_color = _minimum_coloring_qubo(x_vars, chi_lb, chi_ub, magnitude=.75)\n",
    "\n",
    "    # combine all three constraints\n",
    "    Q = Q_neighbor\n",
    "    for (u, v), bias in iteritems(Q_vertex):\n",
    "        if (u, v) in Q:\n",
    "            Q[(u, v)] += bias\n",
    "        elif (v, u) in Q:\n",
    "            Q[(v, u)] += bias\n",
    "        else:\n",
    "            Q[(u, v)] = bias\n",
    "    for (v, v), bias in iteritems(Q_min_color):\n",
    "        if (v, v) in Q:\n",
    "            Q[(v, v)] += bias\n",
    "        else:\n",
    "            Q[(v, v)] = bias\n",
    "\n",
    "    # use the sampler to find low energy states\n",
    "    response = sampler.sample_qubo(Q, **sampler_args) \n",
    "    print(response.info)\n",
    "    computation_time = response.info['timing']['qpu_access_time'] / 10**6 #compute qpu access time, and convert to seconds \n",
    "\n",
    "\n",
    "    # we want the lowest energy sample\n",
    "    sample = next(iter(response))\n",
    "\n",
    "    # read off the coloring\n",
    "    for v in x_vars:\n",
    "        for c in x_vars[v]:\n",
    "            if sample[x_vars[v][c]]:\n",
    "                partial_coloring[v] = c\n",
    "    \n",
    "    return partial_coloring\n",
    "\n",
    "\n",
    "\n",
    "def _chromatic_number_upper_bound(G, n_nodes, n_edges):\n",
    "    # tries to determine an upper bound on the chromatic number of G\n",
    "    # Assumes G is not complete\n",
    "\n",
    "    # chi * (chi - 1) <= 2 * |E|\n",
    "    quad_bound = ceil((1 + math.sqrt(1 + 8 * n_edges)) / 2)\n",
    "\n",
    "    if n_nodes % 2 == 1 and is_cycle(G):\n",
    "        # odd cycle graphs need three colors\n",
    "        bound = 3\n",
    "    else:\n",
    "        if not eigenvalues:\n",
    "            # chi <= max degree, unless it is complete or a cycle graph of odd length,\n",
    "            # in which case chi <= max degree + 1 (Brook's Theorem)\n",
    "            bound = max(G.degree(node) for node in G)\n",
    "        else:\n",
    "            # Let A be the adj matrix of G (symmetric, 0 on diag). Let theta_1\n",
    "            # be the largest eigenvalue of A. Then chi <= theta_1 + 1 with\n",
    "            # equality iff G is complete or an odd cycle.\n",
    "            # this is strictly better than brooks theorem\n",
    "            bound = ceil(max(eigenvalues(nx.to_numpy_matrix(G))))\n",
    "\n",
    "    return min(quad_bound, bound)\n",
    "\n",
    "\n",
    "def _minimum_coloring_qubo(x_vars, chi_lb, chi_ub, magnitude=1.):\n",
    "    \"\"\"We want to disincentivize unneeded colors. Generates the QUBO\n",
    "    that does that.\n",
    "    \"\"\"\n",
    "    # if we already know the chromatic number, then we don't need to\n",
    "    # disincentivize any colors.\n",
    "    if chi_lb == chi_ub:\n",
    "        return {}\n",
    "\n",
    "    # we might need to use some of the colors, so we want to disincentivize\n",
    "    # them in increasing amounts, linearly.\n",
    "    scaling = magnitude / (chi_ub - chi_lb)\n",
    "\n",
    "    # build the QUBO\n",
    "    Q = {}\n",
    "    for v in x_vars:\n",
    "        for f, color in enumerate(range(chi_lb, chi_ub)):\n",
    "            idx = x_vars[v][color]\n",
    "            Q[(idx, idx)] = (f + 1) * scaling\n",
    "\n",
    "    return Q\n",
    "\n",
    "\n",
    "def _vertex_different_colors_qubo(G, x_vars):\n",
    "\n",
    "    Q = {}\n",
    "    for u, v in G.edges:\n",
    "        if u not in x_vars or v not in x_vars:\n",
    "            continue\n",
    "        for color in x_vars[u]:\n",
    "            if color in x_vars[v]:\n",
    "                Q[(x_vars[u][color], x_vars[v][color])] = 1.\n",
    "    return Q\n",
    "\n",
    "\n",
    "def _vertex_one_color_qubo(x_vars):\n",
    "\n",
    "    Q = {}\n",
    "    for v in x_vars:\n",
    "        for color in x_vars[v]:\n",
    "            idx = x_vars[v][color]\n",
    "            Q[(idx, idx)] = -1\n",
    "\n",
    "        for color0, color1 in itertools.combinations(x_vars[v], 2):\n",
    "            idx0 = x_vars[v][color0]\n",
    "            idx1 = x_vars[v][color1]\n",
    "\n",
    "            Q[(idx0, idx1)] = 2\n",
    "\n",
    "    return Q\n",
    "\n",
    "\n",
    "def _partial_precolor(G, chi_ub):\n",
    "\n",
    "    # find a random maximal clique and give each node in it a unique color\n",
    "    v = next(iter(G))\n",
    "    clique = [v]\n",
    "    for u in G[v]:\n",
    "        if all(w in G[u] for w in clique):\n",
    "            clique.append(u)\n",
    "\n",
    "    partial_coloring = {v: c for c, v in enumerate(clique)}\n",
    "    chi_lb = len(partial_coloring)  # lower bound for the chromatic number\n",
    "\n",
    "    # now for each uncolored node determine the possible colors\n",
    "    possible_colors = {v: set(range(chi_ub)) for v in G if v not in partial_coloring}\n",
    "\n",
    "    for v, color in iteritems(partial_coloring):\n",
    "        for u in G[v]:\n",
    "            if u in possible_colors:\n",
    "                possible_colors[u].discard(color)\n",
    "\n",
    "    # TODO: there is more here that can be done. For instance some nodes now\n",
    "    # might only have one possible color. Or there might only be one node\n",
    "    # remaining to color\n",
    "\n",
    "    return partial_coloring, possible_colors, chi_lb\n",
    "\n",
    "\n",
    "def is_cycle(G):\n",
    "\n",
    "    trailing, leading = next(iter(G.edges))\n",
    "    start_node = trailing\n",
    "\n",
    "    # travel around the graph, checking that each node has degree exactly two\n",
    "    # also track how many nodes were visited\n",
    "    n_visited = 1\n",
    "    while leading != start_node:\n",
    "        neighbors = G[leading]\n",
    "\n",
    "        if len(neighbors) != 2:\n",
    "            return False\n",
    "\n",
    "        node1, node2 = neighbors\n",
    "\n",
    "        if node1 == trailing:\n",
    "            trailing, leading = leading, node2\n",
    "        else:\n",
    "            trailing, leading = leading, node1\n",
    "\n",
    "        n_visited += 1\n",
    "\n",
    "    # if we haven't visited all of the nodes, then it is not a connected cycle\n",
    "    return n_visited == len(G)\n",
    "\n",
    "\n",
    "def is_vertex_coloring(G, coloring):\n",
    "   \n",
    "    return all(coloring[u] != coloring[v] for u, v in G.edges)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "corr_mat = corr_tensor[60, :, :].copy()\n",
    "\n",
    "corr_mat[(corr_mat > -1*0.5) & (corr_mat < 0.5)] = 0\n",
    "G, density = make_graph(corr_mat, nodes, 'corr')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8727272727272727"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "density\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\networkx\\drawing\\nx_pylab.py:579: MatplotlibDeprecationWarning: \n",
      "The iterable function was deprecated in Matplotlib 3.1 and will be removed in 3.3. Use np.iterable instead.\n",
      "  if not cb.iterable(width):\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots(figsize=(15,10))\n",
    "\n",
    "nx.draw_shell(G, ax=ax, with_labels=True, node_size=1000, node_color=\"white\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig.savefig('%s_high_density.png'%(dataset))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{}\n"
     ]
    },
    {
     "ename": "KeyError",
     "evalue": "'timing'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-9-f1a8e9ab352c>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mcoloring\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mmin_vertex_coloring\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mG\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msampler\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msamplerSA\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      2\u001b[0m \u001b[0mnum_colors\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmax\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlist\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcoloring\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m<C:\\ProgramData\\Anaconda3\\lib\\site-packages\\decorator.py:decorator-gen-843>\u001b[0m in \u001b[0;36mmin_vertex_coloring\u001b[1;34m(G, sampler, **sampler_args)\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\dwave_networkx\\utils\\decorators.py\u001b[0m in \u001b[0;36m_binary_quadratic_model_sampler\u001b[1;34m(f, *args, **kw)\u001b[0m\n\u001b[0;32m    148\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    149\u001b[0m         \u001b[1;31m# now run the function and return the results\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 150\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0mnew_args\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkw\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    151\u001b[0m     \u001b[1;32mreturn\u001b[0m \u001b[0m_binary_quadratic_model_sampler\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m<ipython-input-4-59f1903d7911>\u001b[0m in \u001b[0;36mmin_vertex_coloring\u001b[1;34m(G, sampler, **sampler_args)\u001b[0m\n\u001b[0;32m    104\u001b[0m     \u001b[0mresponse\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0msampler\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msample_qubo\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mQ\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0msampler_args\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    105\u001b[0m     \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mresponse\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minfo\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 106\u001b[1;33m     \u001b[0mcomputation_time\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mresponse\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minfo\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'timing'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'qpu_access_time'\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m/\u001b[0m \u001b[1;36m10\u001b[0m\u001b[1;33m**\u001b[0m\u001b[1;36m6\u001b[0m \u001b[1;31m#compute qpu access time, and convert to seconds\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    107\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    108\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mKeyError\u001b[0m: 'timing'"
     ]
    }
   ],
   "source": [
    "coloring = min_vertex_coloring(G, sampler=samplerSA)\n",
    "num_colors = np.max(list(coloring.values()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'IYT': 5,\n",
       " 'RWR': 3,\n",
       " 'XLB': 4,\n",
       " 'XLE': 9,\n",
       " 'XLF': 8,\n",
       " 'XLI': 6,\n",
       " 'XLK': 4,\n",
       " 'XLP': 7,\n",
       " 'XLU': 1,\n",
       " 'XLV': 2,\n",
       " 'XLY': 0}"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coloring"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_max_deg(G)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dnx.is_vertex_coloring(G, coloring)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\networkx\\drawing\\nx_pylab.py:579: MatplotlibDeprecationWarning: \n",
      "The iterable function was deprecated in Matplotlib 3.1 and will be removed in 3.3. Use np.iterable instead.\n",
      "  if not cb.iterable(width):\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "coloring\n",
    "\n",
    "\n",
    "colors = []\n",
    "for node in G.nodes():\n",
    "    colors.append(coloring[node])\n",
    "\n",
    "\n",
    "fig,ax = plt.subplots(figsize=(15,10))\n",
    "nx.draw_shell(G, ax=ax, with_labels=True, node_size=1000, \n",
    "                 node_color=list(colors), font_color=\"white\")    # Plot graph density for each threshold. \n",
    "\n",
    "fig.savefig('gc_%s_HD'%(dataset))\n",
    "\n",
    "thresh_array = []\n",
    "density_distr = []\n",
    "\n",
    "for i in np.arange(0.1, 1, 0.1):\n",
    "    density_array = []\n",
    "    for j in range(1, int(num_examples/5)):\n",
    "        corr_mat = corr_tensor[j*5, :, :].copy()\n",
    "        corr_mat[(corr_mat > -1*i) & (corr_mat < i)] = 0\n",
    "        G, density = make_graph(corr_mat, nodes, 'corr')\n",
    "        \n",
    "        density_array.append(density)\n",
    "    \n",
    "    density_distr.append(density_array)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot graph density for each threshold. \n",
    "\n",
    "thresh_array = []\n",
    "density_distr = []\n",
    "\n",
    "for i in np.arange(0.1, 1, 0.1):\n",
    "    density_array = []\n",
    "    for j in range(1, int(num_examples/5)):\n",
    "        corr_mat = corr_tensor[j*5, :, :].copy()\n",
    "        corr_mat[(corr_mat > -1*i) & (corr_mat < i)] = 0\n",
    "        G, density = make_graph(corr_mat, nodes, 'corr')\n",
    "        \n",
    "        density_array.append(density)\n",
    "    \n",
    "    density_distr.append(density_array)\n",
    "    \n",
    "plt.boxplot(density_distr)\n",
    "plt.ylabel(\"Graph Density\")\n",
    "plt.xlabel(\"Correlation Threshold (10^-1)\")\n",
    "plt.title(\"%s Density vs Threshold\" % (dataset))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "no embedding found\n",
      "Error on matrix 5 with threshold 0.500000\n",
      "something went wrong when calculating the chromatic number bounds\n",
      "Error on matrix 10 with threshold 0.500000\n",
      "14.883373260498047\n",
      "'IYT'\n",
      "Error on matrix 15 with threshold 0.500000\n",
      "no embedding found\n",
      "Error on matrix 20 with threshold 0.500000\n",
      "something went wrong when calculating the chromatic number bounds\n",
      "Error on matrix 25 with threshold 0.500000\n",
      "something went wrong when calculating the chromatic number bounds\n",
      "Error on matrix 30 with threshold 0.500000\n",
      "2.8729655742645264\n",
      "'XLB'\n",
      "Error on matrix 35 with threshold 0.500000\n",
      "no embedding found\n",
      "Error on matrix 40 with threshold 0.500000\n",
      "something went wrong when calculating the chromatic number bounds\n",
      "Error on matrix 45 with threshold 0.500000\n",
      "count: 10\n",
      "19.27875280380249\n",
      "'IYT'\n",
      "Error on matrix 50 with threshold 0.500000\n",
      "8.283544301986694\n",
      "'XLB'\n",
      "Error on matrix 55 with threshold 0.500000\n",
      "no embedding found\n",
      "Error on matrix 60 with threshold 0.500000\n",
      "something went wrong when calculating the chromatic number bounds\n",
      "Error on matrix 65 with threshold 0.500000\n",
      "14.843563795089722\n",
      "'XLB'\n",
      "Error on matrix 70 with threshold 0.500000\n",
      "3.341158866882324\n",
      "'IYT'\n",
      "Error on matrix 75 with threshold 0.500000\n",
      "3.513489007949829\n",
      "'IYT'\n",
      "Error on matrix 80 with threshold 0.500000\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\dwave_networkx\\algorithms\\coloring.py:177: ComplexWarning: Casting complex values to real discards the imaginary part\n",
      "  bound = math.ceil(max(np.linalg.eigvals(nx.to_numpy_array(G))))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.5955734252929688\n",
      "'IYT'\n",
      "Error on matrix 85 with threshold 0.500000\n",
      "2.748797655105591\n",
      "'IYT'\n",
      "Error on matrix 90 with threshold 0.500000\n",
      "no embedding found\n",
      "Error on matrix 95 with threshold 0.500000\n",
      "count: 20\n",
      "2.7619664669036865\n",
      "'XLB'\n",
      "Error on matrix 100 with threshold 0.500000\n",
      "3.8538870811462402\n",
      "'XLY'\n",
      "Error on matrix 105 with threshold 0.500000\n",
      "3.953875780105591\n",
      "'IYT'\n",
      "Error on matrix 110 with threshold 0.500000\n",
      "3.515284299850464\n",
      "'IYT'\n",
      "Error on matrix 115 with threshold 0.500000\n",
      "4.701728582382202\n",
      "'IYT'\n",
      "Error on matrix 5 with threshold 0.600000\n",
      "something went wrong when calculating the chromatic number bounds\n",
      "Error on matrix 10 with threshold 0.600000\n",
      "4.8840014934539795\n",
      "'IYT'\n",
      "Error on matrix 15 with threshold 0.600000\n",
      "3.5154855251312256\n",
      "'IYT'\n",
      "Error on matrix 20 with threshold 0.600000\n",
      "something went wrong when calculating the chromatic number bounds\n",
      "Error on matrix 25 with threshold 0.600000\n",
      "no embedding found\n",
      "Error on matrix 30 with threshold 0.600000\n",
      "count: 30\n",
      "('Connection aborted.', OSError(\"(10054, 'WSAECONNRESET')\",))\n",
      "Error on matrix 35 with threshold 0.600000\n",
      "HTTPSConnectionPool(host='cloud.dwavesys.com', port=443): Max retries exceeded with url: /sapi/problems/ (Caused by NewConnectionError('<urllib3.connection.VerifiedHTTPSConnection object at 0x000002290C678C18>: Failed to establish a new connection: [Errno 11001] getaddrinfo failed',))\n",
      "Error on matrix 40 with threshold 0.600000\n",
      "something went wrong when calculating the chromatic number bounds\n",
      "Error on matrix 45 with threshold 0.600000\n",
      "HTTPSConnectionPool(host='cloud.dwavesys.com', port=443): Max retries exceeded with url: /sapi/problems/ (Caused by NewConnectionError('<urllib3.connection.VerifiedHTTPSConnection object at 0x000002290BD897B8>: Failed to establish a new connection: [Errno 11001] getaddrinfo failed',))\n",
      "Error on matrix 50 with threshold 0.600000\n",
      "HTTPSConnectionPool(host='cloud.dwavesys.com', port=443): Max retries exceeded with url: /sapi/problems/ (Caused by NewConnectionError('<urllib3.connection.VerifiedHTTPSConnection object at 0x000002290B61FD30>: Failed to establish a new connection: [Errno 11001] getaddrinfo failed',))\n",
      "Error on matrix 55 with threshold 0.600000\n",
      "no embedding found\n",
      "Error on matrix 60 with threshold 0.600000\n",
      "something went wrong when calculating the chromatic number bounds\n",
      "Error on matrix 65 with threshold 0.600000\n",
      "3.532804250717163\n",
      "'IYT'\n",
      "Error on matrix 70 with threshold 0.600000\n",
      "2.7854228019714355\n",
      "'IYT'\n",
      "Error on matrix 75 with threshold 0.600000\n",
      "3.401357889175415\n",
      "'XLB'\n",
      "Error on matrix 80 with threshold 0.600000\n",
      "count: 40\n",
      "3.360536575317383\n",
      "'IYT'\n",
      "Error on matrix 85 with threshold 0.600000\n",
      "3.8767380714416504\n",
      "'XLI'\n",
      "Error on matrix 90 with threshold 0.600000\n",
      "no embedding found\n",
      "Error on matrix 95 with threshold 0.600000\n",
      "5.012230157852173\n",
      "'XLF'\n",
      "Error on matrix 100 with threshold 0.600000\n",
      "1.3799970149993896\n",
      "1.4217071533203125\n",
      "3.330592632293701\n",
      "4.718587875366211\n",
      "1.4770221710205078\n",
      "'XLP'\n",
      "Error on matrix 105 with threshold 0.600000\n",
      "2.785108804702759\n",
      "'IYT'\n",
      "Error on matrix 110 with threshold 0.600000\n",
      "2.3483715057373047\n",
      "'IYT'\n",
      "Error on matrix 115 with threshold 0.600000\n",
      "3.801171064376831\n",
      "'IYT'\n",
      "Error on matrix 5 with threshold 0.700000\n",
      "no embedding found\n",
      "Error on matrix 10 with threshold 0.700000\n",
      "4.207081317901611\n",
      "'RWR'\n",
      "Error on matrix 15 with threshold 0.700000\n",
      "count: 50\n",
      "5.5277979373931885\n",
      "'XLI'\n",
      "Error on matrix 20 with threshold 0.700000\n",
      "no embedding found\n",
      "Error on matrix 25 with threshold 0.700000\n",
      "no embedding found\n",
      "Error on matrix 30 with threshold 0.700000\n",
      "3.499060869216919\n",
      "'IYT'\n",
      "Error on matrix 35 with threshold 0.700000\n",
      "6.803889036178589\n",
      "'XLI'\n",
      "Error on matrix 40 with threshold 0.700000\n",
      "no embedding found\n",
      "Error on matrix 45 with threshold 0.700000\n",
      "4.92303466796875\n",
      "'XLB'\n",
      "Error on matrix 50 with threshold 0.700000\n",
      "4.111523866653442\n",
      "'IYT'\n",
      "Error on matrix 55 with threshold 0.700000\n",
      "4.20723032951355\n",
      "'IYT'\n",
      "Error on matrix 60 with threshold 0.700000\n",
      "no embedding found\n",
      "Error on matrix 65 with threshold 0.700000\n",
      "count: 60\n",
      "5.9775917530059814\n",
      "'XLE'\n",
      "Error on matrix 70 with threshold 0.700000\n",
      "3.326612710952759\n",
      "'IYT'\n",
      "Error on matrix 75 with threshold 0.700000\n",
      "2.6400809288024902\n",
      "'XLK'\n",
      "Error on matrix 80 with threshold 0.700000\n",
      "3.128770112991333\n",
      "'XLF'\n",
      "Error on matrix 85 with threshold 0.700000\n",
      "3.1406846046447754\n",
      "'XLI'\n",
      "Error on matrix 90 with threshold 0.700000\n",
      "11.131717443466187\n",
      "'IYT'\n",
      "Error on matrix 95 with threshold 0.700000\n",
      "6.1680567264556885\n",
      "'XLI'\n",
      "Error on matrix 100 with threshold 0.700000\n",
      "1.310650110244751\n",
      "1.3403875827789307\n",
      "3.4344916343688965\n",
      "1.3121919631958008\n",
      "3.130798578262329\n",
      "1.3268356323242188\n",
      "4.731554985046387\n",
      "2.2565133571624756\n",
      "1.3299963474273682\n",
      "1.3226377964019775\n",
      "3.197490930557251\n",
      "'XLB'\n",
      "Error on matrix 110 with threshold 0.700000\n",
      "7.341760158538818\n",
      "'XLI'\n",
      "Error on matrix 115 with threshold 0.700000\n",
      "count: 70\n",
      "2.0009963512420654\n",
      "1.8125250339508057\n",
      "1.4771945476531982\n",
      "'XLK'\n",
      "Error on matrix 5 with threshold 0.800000\n",
      "no embedding found\n",
      "Error on matrix 10 with threshold 0.800000\n",
      "2.4830222129821777\n",
      "'XLE'\n",
      "Error on matrix 15 with threshold 0.800000\n",
      "8.129226446151733\n",
      "'XLY'\n",
      "Error on matrix 20 with threshold 0.800000\n",
      "10.198025941848755\n",
      "'XLB'\n",
      "Error on matrix 25 with threshold 0.800000\n",
      "13.075648784637451\n",
      "'IYT'\n",
      "Error on matrix 30 with threshold 0.800000\n",
      "6.249075174331665\n",
      "2.1214308738708496\n",
      "2.784510374069214\n",
      "2.250849723815918\n",
      "2.439901113510132\n",
      "'XLB'\n",
      "Error on matrix 35 with threshold 0.800000\n",
      "1.417665958404541\n",
      "1.420928716659546\n",
      "1.5845391750335693\n",
      "2.4264135360717773\n",
      "2.653630495071411\n",
      "1.4431610107421875\n",
      "1.3667545318603516\n",
      "1.4528744220733643\n",
      "1.408918857574463\n",
      "1.6484873294830322\n",
      "no embedding found\n",
      "Error on matrix 45 with threshold 0.800000\n",
      "6.778523206710815\n",
      "4.144071578979492\n",
      "'XLB'\n",
      "Error on matrix 50 with threshold 0.800000\n",
      "count: 80\n",
      "3.135551929473877\n",
      "2.8389039039611816\n",
      "2.303009271621704\n",
      "4.2073328495025635\n",
      "'XLK'\n",
      "Error on matrix 55 with threshold 0.800000\n",
      "2.5454018115997314\n",
      "'XLU'\n",
      "Error on matrix 60 with threshold 0.800000\n",
      "25.38450837135315\n",
      "'IYT'\n",
      "Error on matrix 65 with threshold 0.800000\n",
      "2.958916664123535\n",
      "1.5824437141418457\n",
      "1.829897165298462\n",
      "1.579200267791748\n",
      "'XLB'\n",
      "Error on matrix 70 with threshold 0.800000\n",
      "6.705453634262085\n",
      "'XLF'\n",
      "Error on matrix 75 with threshold 0.800000\n",
      "2.310591459274292\n",
      "'XLK'\n",
      "Error on matrix 80 with threshold 0.800000\n",
      "2.1241371631622314\n",
      "1.4445533752441406\n",
      "1.7313957214355469\n",
      "1.422391414642334\n",
      "1.4047152996063232\n",
      "1.376636266708374\n",
      "1.3888778686523438\n",
      "1.6186089515686035\n",
      "2.26931095123291\n",
      "1.504119873046875\n",
      "1.6848716735839844\n",
      "1.717576026916504\n",
      "3.2418224811553955\n",
      "'XLI'\n",
      "Error on matrix 90 with threshold 0.800000\n",
      "4.151683807373047\n",
      "'XLF'\n",
      "Error on matrix 95 with threshold 0.800000\n",
      "1.4270508289337158\n",
      "1.3834128379821777\n",
      "4.5947794914245605\n",
      "1.4442055225372314\n",
      "1.4631619453430176\n",
      "1.4085359573364258\n",
      "2.4209907054901123\n",
      "1.4097206592559814\n",
      "1.886681318283081\n",
      "'XLK'\n",
      "Error on matrix 100 with threshold 0.800000\n",
      "count: 90\n",
      "1.3642964363098145\n",
      "1.3930943012237549\n",
      "1.343717336654663\n",
      "4.6704018115997314\n",
      "1.6426317691802979\n",
      "1.3613810539245605\n",
      "1.3516159057617188\n",
      "1.3788745403289795\n",
      "1.6525111198425293\n",
      "1.3544914722442627\n",
      "2.7507681846618652\n",
      "1.8591370582580566\n",
      "'XLK'\n",
      "Error on matrix 110 with threshold 0.800000\n",
      "1.669203281402588\n",
      "2.1620230674743652\n",
      "2.10798716545105\n",
      "1.7595593929290771\n",
      "1.8322482109069824\n",
      "3.0319056510925293\n",
      "1.9822616577148438\n",
      "2.1072404384613037\n",
      "1.637922763824463\n",
      "1.6477186679840088\n",
      "2.3323323726654053\n",
      "1.374511480331421\n",
      "1.3943026065826416\n",
      "1.450291633605957\n",
      "1.573538064956665\n",
      "1.3578917980194092\n",
      "1.9292449951171875\n",
      "1.373589038848877\n",
      "1.3458762168884277\n",
      "1.362518072128296\n",
      "5.227808475494385\n",
      "'XLB'\n",
      "Error on matrix 10 with threshold 0.900000\n",
      "1.499070167541504\n",
      "1.5953290462493896\n",
      "2.3614561557769775\n",
      "1.5062243938446045\n",
      "2.352020025253296\n",
      "1.5912587642669678\n",
      "1.5069739818572998\n",
      "2.303877592086792\n",
      "1.547043800354004\n",
      "2.4888381958007812\n",
      "1.392897605895996\n",
      "1.4856641292572021\n",
      "1.5938963890075684\n",
      "1.8668570518493652\n",
      "1.5760550498962402\n",
      "1.9025163650512695\n",
      "1.3670015335083008\n",
      "1.4312682151794434\n",
      "1.422635555267334\n",
      "1.8041934967041016\n",
      "1.9166264533996582\n",
      "2.0086591243743896\n",
      "'XLV'\n",
      "Error on matrix 25 with threshold 0.900000\n",
      "1.5144233703613281\n",
      "1.7583556175231934\n",
      "2.3634912967681885\n",
      "1.7964482307434082\n",
      "2.770838737487793\n",
      "1.6716187000274658\n",
      "3.066087484359741\n",
      "1.531329870223999\n",
      "2.711648941040039\n",
      "1.6362226009368896\n",
      "'XLI'\n",
      "Error on matrix 30 with threshold 0.900000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.3919336795806885\n",
      "2.348822832107544\n",
      "1.3978424072265625\n",
      "1.38895845413208\n",
      "1.534243106842041\n",
      "1.3439912796020508\n",
      "1.3358733654022217\n",
      "1.3332562446594238\n",
      "2.1508593559265137\n",
      "1.3502881526947021\n",
      "count: 100\n",
      "2.326103687286377\n",
      "1.3337976932525635\n",
      "1.3908321857452393\n",
      "1.4756298065185547\n",
      "1.884209156036377\n",
      "1.3309781551361084\n",
      "2.1782774925231934\n",
      "1.3220198154449463\n",
      "1.3786895275115967\n",
      "1.3554637432098389\n",
      "7.64755916595459\n",
      "'XLI'\n",
      "Error on matrix 45 with threshold 0.900000\n",
      "1.4226856231689453\n",
      "1.3873264789581299\n",
      "1.9291152954101562\n",
      "2.4965553283691406\n",
      "1.420497179031372\n",
      "1.4101715087890625\n",
      "1.4021615982055664\n",
      "1.4641821384429932\n",
      "1.8509337902069092\n",
      "1.3978936672210693\n",
      "2.265096426010132\n",
      "1.4004623889923096\n",
      "1.3890483379364014\n",
      "2.407038450241089\n",
      "1.4950470924377441\n",
      "2.1465399265289307\n",
      "1.3856151103973389\n",
      "1.401947259902954\n",
      "4.776313781738281\n",
      "4.615172863006592\n",
      "2.7513833045959473\n",
      "1.3930776119232178\n",
      "1.3564727306365967\n",
      "1.6227939128875732\n",
      "1.2970287799835205\n",
      "1.3397817611694336\n",
      "2.0826773643493652\n",
      "1.3372607231140137\n",
      "2.822293519973755\n",
      "1.4108026027679443\n",
      "4.149057626724243\n",
      "'XLI'\n",
      "Error on matrix 65 with threshold 0.900000\n",
      "1.2791752815246582\n",
      "2.729079246520996\n",
      "1.3237805366516113\n",
      "1.7332711219787598\n",
      "2.77490234375\n",
      "1.3149974346160889\n",
      "4.545989513397217\n",
      "1.329604148864746\n",
      "1.8508191108703613\n",
      "1.3151886463165283\n",
      "1.5827126502990723\n",
      "2.9569475650787354\n",
      "1.6022913455963135\n",
      "1.3660430908203125\n",
      "1.722076416015625\n",
      "1.4044239521026611\n",
      "2.8257977962493896\n",
      "1.4095590114593506\n",
      "1.484236478805542\n",
      "'XLB'\n",
      "Error on matrix 75 with threshold 0.900000\n",
      "4.470068693161011\n",
      "2.9337966442108154\n",
      "1.4839518070220947\n",
      "1.302203893661499\n",
      "2.1808114051818848\n",
      "1.5214502811431885\n",
      "1.2993578910827637\n",
      "1.605583906173706\n",
      "1.281973123550415\n",
      "1.341104507446289\n",
      "1.479234218597412\n",
      "2.1203808784484863\n",
      "1.2980923652648926\n",
      "1.6819548606872559\n",
      "1.2812087535858154\n",
      "1.5209696292877197\n",
      "1.3115653991699219\n",
      "2.053725242614746\n",
      "1.3219223022460938\n",
      "2.7300546169281006\n",
      "count: 110\n",
      "1.2970709800720215\n",
      "1.3185009956359863\n",
      "4.52904748916626\n",
      "4.999104261398315\n",
      "2.7749195098876953\n",
      "1.317201852798462\n",
      "1.3235676288604736\n",
      "1.8470847606658936\n",
      "1.3035242557525635\n",
      "1.3262286186218262\n",
      "2.317514181137085\n",
      "'XLY'\n",
      "Error on matrix 95 with threshold 0.900000\n",
      "1.2945380210876465\n",
      "1.2990424633026123\n",
      "1.7305076122283936\n",
      "1.275930404663086\n",
      "1.3101537227630615\n",
      "1.2908942699432373\n",
      "2.49649977684021\n",
      "1.3294835090637207\n",
      "2.018406629562378\n",
      "1.343665361404419\n",
      "1.2991278171539307\n",
      "1.3034577369689941\n",
      "2.142860174179077\n",
      "1.337425947189331\n",
      "4.590946197509766\n",
      "1.2880640029907227\n",
      "1.9575402736663818\n",
      "1.4248578548431396\n",
      "1.3246757984161377\n",
      "1.9662718772888184\n",
      "1.4160053730010986\n",
      "1.3035001754760742\n",
      "2.6638681888580322\n",
      "1.321157693862915\n",
      "2.645735740661621\n",
      "1.313995361328125\n",
      "1.3047008514404297\n",
      "1.2958264350891113\n",
      "1.7661099433898926\n",
      "1.3113808631896973\n",
      "1.2983479499816895\n",
      "2.4177138805389404\n",
      "1.2860119342803955\n",
      "1.3073759078979492\n",
      "2.5620923042297363\n",
      "1.3930332660675049\n",
      "1.4698734283447266\n",
      "1.7942886352539062\n",
      "1.3285911083221436\n",
      "1.2913570404052734\n"
     ]
    }
   ],
   "source": [
    "# Create graph for each date and calculate best coloring using quantum computer. \n",
    "\n",
    "import time\n",
    "\n",
    "coloring_array = []\n",
    "valid_coloring_array = []\n",
    "num_colors_array = []\n",
    "date_array = []\n",
    "density_array = []\n",
    "threshold_array = []\n",
    "\n",
    "count = 0\n",
    "for i in np.arange(0.5, 1, 0.1):\n",
    "    for j in range(1, int(num_examples/5)):\n",
    "        \n",
    "        corr_mat = corr_tensor[j*5, :, :].copy()\n",
    "        corr_mat[(corr_mat > -1*i) & (corr_mat < i)] = 0\n",
    "        \n",
    "        G, density = make_graph(corr_mat, nodes, 'corr')\n",
    "        \n",
    "        count += 1\n",
    "        if count % 10 == 0: \n",
    "            print(\"count: %d\" % (count))\n",
    "            \n",
    "        try:\n",
    "            opt_coloring = {}\n",
    "            min_colors = dim\n",
    "            \n",
    "            for k in range(10):\n",
    "                t = time.time()\n",
    "                coloring = dnx.min_vertex_coloring(G, sampler)\n",
    "                elapsed = time.time() - t\n",
    "                print(elapsed)\n",
    "                num_colors = np.max(list(coloring.values())) + 1\n",
    "                valid_coloring = dnx.is_vertex_coloring(G, coloring)\n",
    "                \n",
    "                if valid_coloring and num_colors < min_colors:\n",
    "                    opt_coloring = coloring\n",
    "                    min_colors = num_colors\n",
    "            \n",
    "            if opt_coloring == {}:\n",
    "                raise Exception\n",
    "                \n",
    "        except Exception as err:\n",
    "            print(err)\n",
    "            print(\"Error on matrix %d with threshold %f\" % (j*5, i))\n",
    "        else:\n",
    "            \n",
    "            coloring_array.append(opt_coloring)\n",
    "            num_colors_array.append(min_colors)\n",
    "            valid_coloring_array.append(valid_coloring)\n",
    "            \n",
    "            threshold_array.append(i)\n",
    "            density_array.append(density)\n",
    "            date_array.append(dates[j*5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "assert len(coloring_array) == len(date_array) == len(density_array) == len(threshold_array) == len(num_colors_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create Pandas DataFrame for quantum results\n",
    "pd.DataFrame(data={\"date\": date_array, \"threshold\": threshold_array, \"density\": density_array,\n",
    "                \"coloring\": coloring_array, \"num_colors\": num_colors_array, \n",
    "                \"valid_coloring\": valid_coloring_array}).to_csv(\"grphcolor_quant_%s_res.csv\" % (dataset))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'threshold_array' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-26-94e9c863fa73>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      7\u001b[0m \u001b[0mdensity_array\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      8\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 9\u001b[1;33m \u001b[1;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mthreshold_array\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     10\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     11\u001b[0m     \u001b[1;31m# get threshold and matrix idx\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mNameError\u001b[0m: name 'threshold_array' is not defined"
     ]
    }
   ],
   "source": [
    "# Run classical graph coloring algm on the matrices that ran successfully above\n",
    "from networkx.algorithms.coloring import greedy_color\n",
    "\n",
    "coloring_array = []\n",
    "valid_coloring_array = []\n",
    "num_colors_array = []\n",
    "density_array = []\n",
    "time_array = []\n",
    "\n",
    "for i in range(len(threshold_array)):\n",
    "    \n",
    "    # get threshold and matrix idx \n",
    "    thresh = threshold_array[i]\n",
    "    idx = dates.tolist().index(date_array[i])\n",
    "    \n",
    "    corr_mat = corr_tensor[idx, :, :].copy()\n",
    "    corr_mat[(corr_mat > -1*thresh) & (corr_mat < thresh)] = 0\n",
    "\n",
    "    G, density = make_graph(corr_mat, nodes, 'corr')\n",
    "\n",
    "    try:\n",
    "        t = time.clock()\n",
    "        coloring = greedy_color(G, strategy='independent_set')\n",
    "        computation_time = time.clock() - t\n",
    "        valid_coloring = dnx.is_vertex_coloring(G, coloring)\n",
    "    except Exception as err:\n",
    "        print(\"Error on matrix %d with threshold %f\" % (j*5, i))\n",
    "    else:\n",
    "        num_colors = np.max(list(coloring.values())) + 1\n",
    "\n",
    "        coloring_array.append(coloring)\n",
    "        num_colors_array.append(num_colors)\n",
    "        valid_coloring_array.append(valid_coloring)\n",
    "        time_array.append(computation_time)\n",
    "        density_array.append(density)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create Pandas DataFrame for classical results\n",
    "pd.DataFrame(data={\"date\": date_array, \"threshold\": threshold_array, \"density\": density_array,\n",
    "                \"coloring\": coloring_array, \"num_colors\": num_colors_array, \n",
    "                \"valid_coloring\": valid_coloring_array}).to_csv(\"grphcolor_class_%s_res.csv\" % (dataset))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Compare classical vs quantum\n",
    "quant_res_df = pd.read_csv(\"grphcolor_quant_%s_res.csv\" % (dataset))\n",
    "class_res_df = pd.read_csv(\"grphcolor_class_%s_res.csv\" % (dataset))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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wFOhjZkVJ05qzbxuK4Qgz289Cb341hKtKW919CfAc8Csz62VmeWa2l5kdHi16F/A9Mzso+gwMN7NEZbaUcD9FwuPASWZ2VHRm87uEyiRtRWxme5vZkVHSXEs4+7s1mjfJzDKRnDfHW0CNhaFfuppZvpnta2afiWI5x8xKoiuka6Jltu7qRj109d6joUcjiz5A+Fz3jj4HFxCazu3AzAab2aDof3cwodnNj6PtryfcB3O9mXU3s0MIP/Ae3NX3JtIauPsaQrPxO8zsdDPrER3jxhGaZDamJ7DK3WvNbALhvv5UP4rqnn0I96m1uC5Lla6+aMZxurH19TezU6KTW5sIV1AaOn6lHtMhtEI4kFBXP9DE5h4l1GMX8+nVxAbrn6Ziz7D/AX4Q/a8wsyILvbsnYnzZzK5Lt6CZnWFmiRPvqwlJ01bCvXYjzezc6LdDoZl9xsxGR/XFPcAt0TE438w+G9V3ywnNH5P39SPAZWa2h5n1ILQYeszd6xqIqcF9amEcz5cb2A/ptt0iTX0eG9lfTa331cbqRHd/NSr6EOHK9WHR5/p64El3T3sVMPr9km9mJYQrn3+NrjRC+Ex/w8zGmFlvwr2r9+3MfumIlCi2Ll8l3DO1MDpbU+XuVYTL6WdbSpMWd38G+A2h45hywplVCBVFYqDdBq8cuPtjhCuY5xDOHq0gJAJTgD81Euf3CBXqWsJZy3QV5/8SOtkoA/5O6Dmrxdz9FuBywhd7eRTnpYSKDcL9WdMJPaD9m9Bs9mdp1rOZ0EzmBML7vAP4StKBJJ1SQpOcxrxr4cpQOaFH2Mvc/dpom2sJvb8+TjiQnkU4e52I6QNCxTHXQtOOQTSxby2MIXl1A7EMINxfUkNoHvQKnybNXyEkrrOjWJ4ganbs7n8iNF98ONruXwgdEUHooOGaKL7vufuHhM/Lbwn78WRCj3mbG4ipM/DLqGwV4YpdIv5SPv3Mxiq6unYy4eTLvCieuwgdvkDoEGNW9L+8jXAPYm1T640qsbRXBnfRjwnNmRYQ/o83u/s/om0OtXDmdWhUdi9Cor6ecGXgKndPHmD7EkLHCMsIn7eL3V1XFKXdcPebCPXEFYTP+VLCj8UraeAkVuQSwkmUtYSTjI+nKfMK4fj+AvDfKd+tlmqwvog0eJxuQh7hpN1iQnPLwwnvLZ3rgPujY/qXILRKILR+2YNwYqlBUQLxBuEKV3L91Fj9kxXu/hShRcijFm7deJ9Q5yc0Vqd/Bngz+v88Tbhvf15Ujx8LTCbs36poG4lx+L5H+O3xNmHf30joC2EDUS+i0b4+mJBUPki4J34e4eTptxp5S43t0wbfSwPb3hmNfR7T7q+d3M4OojrqIkLCuIxwUmfbZzrNb6HbCCd5P4z+XpC0rn8Q7i9+iVCnLiA6mSpNS/R2JO2AmY0mHBg7N3SGKktxOKHpZHmuYsgEM3uOcPCbk+tY2iMzuwv4k7s/m+tYRESSWRjPeB6hE66c1afZYmbXEobROSfXscQhuvr1J3f/bK5jyQQzKyMM/6DmkxIrJYptnJl9gXDFrjvhakK9uzd2T182YmoXiaKIiHRMHSlRNLPdCB1inevu/8x1PCLSeqjpadv3TUKTzE8I7cObfU+biIiIdFxmdgHhlo5nlCSKSCpdURQREREREZHt6IqiiIiIiIiIbEeJooiIiIiIiGynoOkibUffvn192LBhuQ5DRERiNmPGjBXuXpLrONoK1Y8iIh1HpurIdpUoDhs2jOnTp+c6DBERiZmZLch1DG2J6kcRkY4jU3Wkmp6KiIiIiIjIdpQoioiIiIiIyHaUKIqIiIiIiMh2lCiKiIiIiIjIdpQoioiIiIiIyHbaVa+nIiLNUV9fz4oVK1izZg1bt27NdTiSRn5+PsXFxfTt25e8PJ3TFBERyTYliiLS4VRUVGBmDBs2jMLCQsws1yFJEndny5YtLF26lIqKCoYOHZrrkERERDqc2E7TmlkXM3vLzN41s1lm9pM0ZTqb2WNmVm5mb5rZsKR5P4imf2hmx8UVp4h0POvXr2fw4MF06tRJSWIrZGZ06tSJwYMHs379+lyHIyIi0iHF2Z5nE3Cku48FxgHHm9nBKWW+Aax29+HArcCNAGY2BpgM7AMcD9xhZvkxxioiHYyaM7Z++h+JiIjkTmy1sAfropeF0cNTip0K3B89fwI4ysLp/VOBR919k7vPA8qBCXHFmm319fCPf4Cn7g0REZEObv6K9XyyfF3TBUVEJFaxnq41s3wzKwOWAc+7+5spRQYDiwDcvQ6oBvokT49URNPSbeNCM5tuZtOXL1+e6bcQi/vugxNOgAcfzHUkItIenHfeeZx//vm5DmMH1113HUcffXSuw5A2ZtJ/v8xRv3ol12GIiHR4sSaK7r7V3ccBQ4AJZrZvSpF0Nwd5I9PTbWOKu4939/ElJSW7FnCWJPLZN97IbRwi0jZMnz6d0047jZKSEnr16sXIkSP5zne+w5IlS3IdGgsXLiQ/P58jjzwy16FIO7N+U12uQxAR6dCycgOIu68BXibcb5isAigFMLMCoAhYlTw9MgRYHHugWXLSSeHv/Pk5DUNE2oDnn3+eQw89lL333puysjJqamp45ZVX6NOnD6+8kvurLnfddRfFxcW89NJLfPTRR7kOR9qBU8YOAuC9iuocRyIi0rHF2etpiZkVR8+7AkcDH6QUexr4avT8dOBFd/do+uSoV9Q9gBHAW3HFmm377gvf+x4MHJjrSESktbvkkks466yzuPHGGxk8OLTAHzhwID/60Y+YPHly2mWuvvpq9txzT3r06MFee+3Fr3/9623zNm/ezIUXXki/fv22XZ184oknAJg/fz7HHXccxcXF9O7dm4MOOogPP/ywwdi2bt3KPffcww9+8AP23XdfpkyZ0uh7qaqq4uSTT6aoqIiRI0dy9913Y2bM11kzSfKTU/ZhzMBebN5an+tQREQ6tDjHURwI3B/1VpoHPO7ufzOz64Hp7v40cDfwoJmVE64kTgZw91lm9jgwG6gD/p+7t5tRscvK4NJLYffdcx2JiCSbNGnHaV/6ElxyCWzYACeeuOP8884LjxUr4PTTd5x/8cVw5pmwaBGce26Y9vLLzYvno48+ory8nN///vfNWyAyZswYXnvtNQYOHMhLL73ESSedxOjRoznuuOO47777ePvtt5kzZw59+vRh0aJFrF27FggJ5tChQ3n66acpKChg1qxZFBcXN7idv/71ryxdupRzzz2X/Px8fvGLX/Dzn/+czp07py1/9tlnU1xczKJFi6itreVLX/pSi96XtH/VG7ewcNUG/nzx5+jaSZ2di4jkUpy9nr7n7ge4+/7uvq+7Xx9NvzZKEnH3Wnc/w92Hu/sEd5+btPzP3X0vd9/b3Z+JK85cOOssuPzy8LxeJ0xFpAGJDroSVxKb65xzzmHQoEGYGUceeSQnnXQSL7zwAgCdOnVi3bp1zJ49m7q6OkpLSxkzZsy2eVVVVcydO5f8/Hz2339/+vfv3+B2pkyZwkknnUT//v0599xzqamp4cknn0xbtqKighdffJGbb76ZXr160a9fP370ox+16H1J+/fOgtWcevvrzKmqob7ecXUPLiKSM3FeUZQGVFTA0UfDuHHhCkZSqzARyaHGrvR169b4/L59G59fWtr8K4kJiQ66KisrGT16dLOX+81vfsMf/vAHKioqcHc2btzIWWedBYQkcunSpVx22WV8/PHHHHXUUdx0000MHz6cm2++mZ/+9KecfPLJrF+/ntNPP50bbriBHj167LCNBQsW8Oyzz/LUU08B0LdvX0455RTuvPNOvvzlL+9QvrKyEoChQ4dum7Z7B29WYWbHA7cB+cBd7v7LlPmdgQeAg4CVwJnuPt/Mzga+n1R0f+BAdy/LTuTxWVJdC8C7i9bwlbvf4rnLPs+g4q45jkpEpGPSaMZZVlMDa9eGH429esG0abmOSERaq5EjRzJ8+HAeeeSRZi/z+uuvc+WVV3LnnXeyYsUK1qxZw8knn7ztykxBQQFXXnkl06dPZ8GCBXTr1o2vf/3rQEhMf/Ob31BeXs7rr7/Oyy+/zE033ZR2O3/4wx+or6/n/PPPZ8CAAQwYMIBnn32WV155Je19jYmrogsXLtw2Lfl5RxPdlnE7cAIwBviymY1JKfYNYLW7DwduBW4EcPeH3H1c1Kv4ucD89pAkAlRVbyTPYP8hRazbVEfZojW5DklEpMNSophl0Ul1Bg+GiRNh5kzYtCm3MYlI63XHHXfw0EMPcfXVV7N4cej8edmyZdxwww089thjO5SvqakhPz+fkpISzIy///3vPPPMp633X3zxRWbMmMGWLVvo2rUr3bt3p6AgNC557LHHmDdvHu5OUVERnTp12jYvWV1dHffeey9XXXUV7733HmVlZZSVlfHRRx8xatSotJ3aDBkyhEmTJnHVVVexdu1ali1bxs9+9rNM7aa2aAJQ7u5z3X0z8ChwakqZU4H7o+dPAEeZWerwUV8Gmn8moZVbUl1LSc/O7Du4iE75eUoURURySIliliUSxSFDQqK4eTO8+25uYxKR1uuYY47htddeY/bs2ey333707NmTQw45hGXLlnH44YfvUP64447j3HPPZcKECfTt25cnnniCL3zhC9vmJzqf6d27NwMHDmTBggXceeedAMycOZPDDz+cHj16sM8++3DggQfyve99b4dt/PWvf2XVqlVcdtll264mJh6XXXYZ999/P5vSnAF7+OGH2bBhA0OGDOHQQw/ljDPOAGiw85t2bjCwKOl1RTQtbRl3rwOqgT4pZc6kHSWKVTW1DCjqSueCfMYM6kXZQiWKIiK5Yu3pRvHx48f79OnTcx1Go5Ytg1dfhSOPhHXrYOhQ+M1v4FvfynVkIh3HnDlzWnTPn8Tj2Wef5dRTT2Xjxo3seKEsaOh/ZWYz3H183DHGxczOAI5z9/Oj1+cCE9z9W0llZkVlKqLXn0RlVkavJxLubdyvgW1cCFwIMHTo0IMWLFgQ51vKiBkLVrNpy1Y+N7wv1z09i8feXsS/rzuWgnyd1xYRaa5M1ZHqzCbL+vWDL34xPC8uhu98J4yrKCLS3r377ruYGfvttx/z5s3jmmuu4cwzz2wwSWznKoDSpNdDgMUNlKkwswKgiDCUVMJkGrma6O5TgCkQTqRmIObYHbR7723Pj92nPz27FLCprl6JoohIDihRzLJp02DLFjjsMDCDW2/NdUQiItmxatUqLrjgApYsWUJRUREnnHACv/rVr3IdVq68DYwwsz2ASkLSd1ZKmaeBrwJvAKcDL3rUDMjM8oAzgM9nLeKY1W7ZyssfLmNcaW8GFHXhc3v15XN79c11WCIiHZYSxSz7+c/DwNtlUf909fXw8cfhnsXu3XMbm4hInI444gjKy8tzHUar4O51ZnYp8CxheIx73H2WmV0PTI/GG74beNDMyglXEicnreLzQEXy+MNtXeWajVz0x3f49ZnjOO2AcLvm+k11LK2pZc+SHYdoERGReClRzLLKypAUJrz6ahhLcepUOOGEnIUlIiJZ5u5Tgakp065Nel5LuGqYbtmXgYPjjC/blkZjKA4o6rJt2n89MpOFqzbw/OU7dtwkIiLxUqP/LKuoCENjJBx0EOTlwZtv5i4mkY6oPXXk1V7pf9SxLEkkir0+TRTHlhZTvnwda2u35CosEZEOS4liFm3aBMuXb39FsUcP2GcfJYoi2VRYWMjGjRtzHYY0YePGjRQWFuY6DMmSqpodryiOKy3GHd6rqM5VWCIiHZYSxSyKxsre7ooihPEU33oLdPJcJDv69etHZWUlGzZs0FWrVsjd2bBhA5WVlfTr1y/X4UiWVFXXUtytkC6F+dumjS0tBqBskcZTFBHJNt2jmEUDB4ZeT4cN2376xIlw111QXg4jRuQkNJEOpVevXgAsXryYLVvUpK01KiwspH///tv+V9L+XTxpL75w4PZnUou6FrJnSXdmLlSiKCKSbUoUs6hLl5AUpjrhBHjqKRgwIPsxiXRUvXr1UhIi0ooMKu7KoOKuO0z/ySn70LtbpxxEJCLSsSlRzKJp0+CDD+ArXwkd2CQMHrxjc1QREZGO5KE3F7D/4GL2G1K03fTDRpTkKCIRkY5N945TI4wAACAASURBVChm0aOPwre+BWY7znvvPXjggezHJCIikmub6+r54VPv88IHS9PO+9t7i3m/Uh3aiIhkkxLFLKqsDFcO0yWKjzwC3/gGqCNGERHpaJatDT2eDkzq8TTBDL77+Ls8NbMy22GJiHRoShSzqKJi+6Exkk2cCHV1MHNmdmMSERHJtapoDMX+vXZMFAvz89h3cJF6PhURyTIlilmUuKKYTqKTG42nKCIiHU1iDMWBRTt2ZgNwQGkx71dWs7muPpthiYh0aEoUs2Tr1jCOYkNXFAcOhNJSJYoiItLxJK4oDkjT9BRg3NBiNtXV80FVTTbDEhHp0NTraZbk5cHChVBY2HCZgw+GGTOyF5OIiEhrcM7Bu3PkqH706pL+Z8m40mIA/l1Zzf5DirMZmohIhxVbomhmpcADwACgHpji7rellPk+cHZSLKOBEndfZWbzgbXAVqDO3cfHFWs2mMGgQY2Xue02KFb9JyIiHUyXwnz2LOnR4PzBxV159YojGNI7fdNUERHJvDibntYB33X30cDBwP8zszHJBdz9Zncf5+7jgB8Ar7j7qqQiR0Tz23SSCFBWBj/9Kaxa1XCZgQOhq+pAERHpYO7/13ye+feSBuebGaW7dcPSdRsuIiKxiC1RdPcl7v5O9HwtMAdobFj5LwOPxBVPrr32Glx7LWzZ0ni5a66Be+/NTkwiIiKtwZR/zuW52TuOoZjs3xXVXP5YGdUbmqhIRUQkI7LSmY2ZDQMOANJ21WJm3YDjgT8nTXbgOTObYWYXxh1j3Coqwv2JJSWNl5s6FR5+ODsxiYiI5Fp9vbO0prbBjmwSamq38OTMSsoqNEyGiEg2xJ4omlkPQgL4HXdvqLuyk4HXU5qdHuLuBwInEJqtfr6B9V9oZtPNbPry5cszGnsmVVaGexTzmtjjEyfCW29BvXoAFxGRDmDl+s3U1TsD0oyhmGz/IUWYQdlCJYoiItkQa6JoZoWEJPEhd3+ykaKTSWl26u6Lo7/LgKeACekWdPcp7j7e3ceXNHW5LocqKhoeGiPZxIlQUwMffhh/TCIiIrnW1NAYCT27FDKiXw/KFq3ORlgiIh1ebImihTvO7wbmuPstjZQrAg4H/jdpWncz65l4DhwLvB9XrNlQVQWDG7tDMzJxYvg7bVq88YiIiLQGy9dFiWITVxQhDJNRtmgN7h53WCIiHV6c4ygeApwL/NvMyqJpVwNDAdz9f6JpXwCec/f1Scv2B56KejcrAB5293/EGGvs3n8fNm5sutzee8Mee8DatfHHJCIikmtHjurP7OuPo1N+0+euDxzam5kL17B6wxZ2694pC9GJiHRcsSWK7v4a0GQ/1u5+H3BfyrS5wNhYAsuR/Hzo0fAQUdvk5cEnn4RxF0VERDqCbp2a93PkzM+UMnnC0JijERERyFKvpx3dvHnwzW/C7NnNK68kUUREOooH35jP7S+VN6usxlEUEckeJYpZ8MEHMGUKrGlmR23vvgtjxsCrr8Ybl4iISK49834VL8xpfAzFZDc8M4ev3vNWjBGJiAgoUcyKysrwtzm9ngIMHAhz5qhDGxERaf+qamoZWNS1Rcu88clKNtVtjSkiEREBJYpZUVERmpMOHNi88v36hQ5t3nwz3rhERERyyd2pqq6lfzN6PE04oLSYzVvrmb24oaGZRUQkE5QoZkFlJfTvD4WFzV9m4kQliiIi7ZmZHW9mH5pZuZldlWZ+ZzN7LJr/ppkNS5q3v5m9YWazzOzfZtb8TKsVWbupjg2btzKwiTEUk40r7Q1A2aJm3s8hIiI7RYliFmzaFK4QtsTEieFK5OLF8cQkIiK5Y2b5wO3ACcAY4MtmNial2DeA1e4+HLgVuDFatgD4I3CRu+8DTAK2ZCn0jFq9fjPF3Qrp34JEcUBRFwb06qJEUUQkZnGOoyiRBx6Alo4NPGkSnHtuSDJFRKTdmQCUR8NBYWaPAqcCyf1jnwpcFz1/AvidhW4/jwXec/d3Adx9ZbaCzrTd+3Sn7Npj8RZWkmd+ppSeXfQTRkQkTjrKZklLe/QeNy4kmCIi0i4NBhYlva4AJjZUxt3rzKwa6AOMBNzMngVKgEfd/ab4Q45PS4e9uOyYkTFFIiIiCWp6GrMNG+DEE+GZZ1q+rDtUVWU+JhERybl0mVHqZbWGyhQAhwJnR3+/YGZH7bABswvNbLqZTV++fPmuxhuLP01fxKUPv0N9fQub3QC1W7ZSvbFNtrgVEWkTlCjGrLIyJIkrVrR82SuvhBEjYKt6ABcRaW8qgNKk10OA1LvSt5WJ7kssAlZF019x9xXuvgGYChyYugF3n+Lu4919fElJSQxvYde9s3AN0+auJC+vZVcUa7dsZexPnuPuV+fGFJmIiChRjFlFRfg7eHDLl91/f1i3DmbPbrqsiIi0KW8DI8xsDzPrBEwGnk4p8zTw1ej56cCLHm7mexbY38y6RQnk4Wx/b2ObUVW9sUVDYyR0Kcxnj77dmakObUREYqNEMWaJRHHIkJYvOzG6W0XDZIiItC/uXgdcSkj65gCPu/ssM7vezE6Jit0N9DGzcuBy4Kpo2dXALYRkswx4x93/nu33kAlLqmtbNDRGsgOGFvPuojU71WxVRESapkQxZpWV4e/OXFEcPhx22w2mTctsTCIiknvuPtXdR7r7Xu7+82jate7+dPS81t3PcPfh7j4h0UNqNO+P7r6Pu+/r7lfk6j3sqqU1tTt1RRFgXGkxNbV1zF2xPsNRiYgIKFGMXadOsN9+0L17y5c1gwkTdEVRRETan7qt9Qwo6sqeJT12avlxpb0BNJ6iiEhMNDxGzC6/PDx21mWXwdq1mYtHRESkNSjIz+OZbx+208sP79eDa04azYFDizMYlYiIJChRbOWOPTbXEYiIiLQ++XnG+YftmeswRETaLTU9jdnRR8Ovf71r63jrLZg+PTPxiIiItAbPz17KF3//L5bW1O70OtZs2Myzs6qo3aJxpEREMk2JYoy2bIEXX4TVq3dtPeecAz/7WWZiEhERaQ0+Wb6OGQtW073zzjduenv+ar754Azer6zOYGQiIgJKFGNVVQXuOzc0RrKJE0OHNq4ewEVEpJ2oqq6lZ+cCeuxCojiuNNyfqA5tREQyT4lijBJjKO7M0BjJJk4MSeeiRbsek4iISGtQVV1L/50cQzGhpGdnBhd3ZaYSRRGRjFOiGKPEGIqZuKIIGiZDRETajyU1tQzcxUQRYNzQYsoWKlEUEck0JYox6tYNDj101xPFsWOhc2cliiIi0n6M6NeDA4f23uX1HFBaTOWajSxfuykDUYmISEJsw2OYWSnwADAAqAemuPttKWUmAf8LzIsmPenu10fzjgduA/KBu9z9l3HFGpcTTwyPXdWpE7z+OowcuevrEhERaQ3++4yxGVnPqeMGc8SofvTp3ikj6xMRkSDOcRTrgO+6+ztm1hOYYWbPu/vslHKvuvt/JE8ws3zgduAYoAJ428yeTrNsh3HQQbmOQEREpPUp6dmZkp6dcx2GiEi7E1vTU3df4u7vRM/XAnOA5nbrMgEod/e57r4ZeBQ4NZ5I43PyyXDeeZlZ1+LF8KMfwUcfZWZ9IiIiufLuojV89oYXeHv+qoys77lZVdz5yicZWZeIiARZuUfRzIYBBwDp7rL7rJm9a2bPmNk+0bTBQHIfnxU0P8lsNWbNCmMpZsKmTWEsxRdfzMz6REREcmXxmo0sqa6lW6f8jKzvnx8v57cvlrO1XuNIiUjmuDt3vFxOxeoNuQ4lJ2JPFM2sB/Bn4DvuXpMy+x1gd3cfC/wW+EtisTSrSnv0N7MLzWy6mU1fvnx5psLeZe6h19Nd7cgmYdgwKCmBadMysz4REZFcqaqpBWBAr13v9RRgXGlv1m2qo3zZuoysT0QEYP7KDdz0jw+54ZkPch1KTsSaKJpZISFJfMjdn0yd7+417r4uej4VKDSzvoQriKVJRYcAi9Ntw92nuPt4dx9fUlKS8fews1asgM2bM5comoVhMtTzqYiItHVV1bV0ys9jtwx1QDOutBiAskWrM7I+ERGABSvXA3De54blNpAciS1RNDMD7gbmuPstDZQZEJXDzCZE8awE3gZGmNkeZtYJmAw8HVescUiMoTg4gw1mJ06EDz6ANRouSkRE2rCqmlr6F3Um+gmwy/bs252eXQooW6QKUkQyZ/6KkCju3qdbjiPJjTivKB4CnAscaWZl0eNEM7vIzC6KypwOvG9m7wK/ASZ7UAdcCjxL6ATncXefFWOsGde5M0yeDKNGZW6dBx8MPXtCeXnm1ikiIpJt+w0u4sT9BmZsfXl5xrjSYo2lKCIZNX9luDfxK3e/xcdL1+Y4muyLbXgMd3+N9PcaJpf5HfC7BuZNBabGEFpWjB4NjzyS2XUecQSsXg35mbn3X0REJCfOP2zPjK/znvM+Q2F+VvroE5EOpF/PznxQtZaZC9cwon/PXIeTVTqixmTr1syvMz9fSaKIiLRt7h5L76RKEkUk0647ZR+m/eAoenUpYGYHbNquo2pMzj8f9tmn6XIt9cADcOSRoVdVERGRtmb1hi2MvOYZHnlrYUbXu2VrPeffP52H3lyQ0fWKSMeWl2eMLS1m5sKO11mWEsWYVFZCjx6ZX++GDfDSSzBvXubXLSIiEreq6lq21jtFXQszut7C/Dw+XraWVz9akdH1ikjHtGjVBr5wx+u8OXclB5QW89HStazfVJfrsLJKiWJMKioyNzRGsokTw18NkyEiIm1RVc1GAAYUZWYMxWTjSovV86mIZET58nXMXLiGvDzjc8P7cvLYQaxToiiZUFkZT6K4337QtasSRRERaZuqqkPPpANjShSramqpqq7N+LpFpGNJDI0xrE93Dt6zD7dNPoD+vTJ/3GrNlCjGoKYmPDI5hmJCQQEcdJASRRERaZuqqjeSZ1DSo3PG1z2utBiAskUd714iEcmsBSs30KNzAX17dAJCR1yr12/OcVTZpUQxBvX18P3vwyGHxLP+k0+GvfdWhzYiItL2jC0t5oLD9qQghl5KxwzqxYRhu1GQp583IrJr5q1Yz7C+3TALo/398C/vc/xt/8xxVNkV2ziKHVlxMdx0U3zrv+KK+NYtIiLZYWbHA7cB+cBd7v7LlPmdgQeAg4CVwJnuPt/MhgFzgA+jotPc/aJsxb2rjhrdn6NG949l3Z0L8nn8os/Gsm4R6ViG7taNUQM+HTdxRL8ePPzmQpZUb2RgUdccRpY9ShRjUFMDZtAz5jE5a2uhS8dqKi0i0i6YWT5wO3AMUAG8bWZPu/vspGLfAFa7+3AzmwzcCJwZzfvE3cdlNegMWb52E727FcZyRTFhc109BXlGXp7Ftg0Rad9+etq+273e1rR94RoG7tcxEkW1zYjBb38LvXqFRC4un/lMGKtRRETapAlAubvPdffNwKPAqSllTgXuj54/ARxliTZQbdiRv3qZn/19Tmzrf/nDZex73bPMqaqJbRsi0vGMGdSLTvl5HapnZSWKMaiogD594r3aN2SIOrQREWnDBgOLkl5XRNPSlnH3OqAa6BPN28PMZprZK2Z2WNzBZsr6TXWsra2LtefAYX26s7muvkP9mBORzHrpg2Uc/IsX+Gjp2m3TOhfkM3pQL2Z2oGOLEsUYxDWGYrKJE6G8HFaujHc7IiISi3RXBlO7KGuozBJgqLsfAFwOPGxmvXbYgNmFZjbdzKYvX758lwPOhKqa0NQmjqExEnbv043e3QopW9hxfsyJSGbNXbGeqppa+nTvtN30iw/fk68fskeOoso+JYoxqKyMZ2iMZAcfHP6+9Va82xERkVhUAKVJr4cAixsqY2YFQBGwyt03uftKAHefAXwCjEzdgLtPcffx7j6+pKQkhrfQconxDeO8omhmjCst1hVFEdlp81esp2eXAnZLSRSP33cgx+87IEdRZZ8SxRhk44ri+PGQl6fmpyIibdTbwAgz28PMOgGTgadTyjwNfDV6fjrworu7mZVEneFgZnsCI4C5WYp7lyQSxTivKAKMK+1N+fJ1rK3dEut2RKR9mr9yPXv07U7qbeHuznsVa7ZrktqeqdfTDHOHa6+FUaPi3U6PHvDTn8Jn1Qu4iEib4+51ZnYp8CxheIx73H2WmV0PTHf3p4G7gQfNrBxYRUgmAT4PXG9mdcBW4CJ3X5X9d9FyYwb14vvH7c2AmBPFo0b3oyDfqK+PdTMi0k7NX7mecaW908477963OXp0P246fWyWo8o+JYoZZgaXXpqdbV19dXa2IyIimefuU4GpKdOuTXpeC5yRZrk/A3+OPcAYjB7Yi9EDd7idMuP2HVzEvoOLYt+OiLQ/7s4xowew7+Adj1VmxtghRczsIPdAq+lphq1ZA3PmwObN8W+rrg5mzoRVbeI8soiIdHRzl69j2doYx45Ksnr9Zv5dUZ2VbYlI+2FmXHvyGP7zwPT3kXWkpu1KFDPsH/+AMWPg44/j39acOXDggTB1atNlRUREcu3bj5bx/T+9l5Vt/fTvs/nafW/jntqZrIhIw2q3bGXL1obbrY8bWow7vNcBTkQpUcywiorwN+7ObCAkpD16qEMbERFpG5ZU18bekU3CAaXFrFi3ico1G7OyPRFpH/44bQGjfvQPqjekv2I4bkgxQIfoWVn3KGZYZSV07w694r8Fg/z80PvptGnxb0tERGRXbK6rZ+X6TbF3ZJOQ6IiibNEahvTulpVtikjbN3/lerp3yqdX1/RpUlG3Qp646LPsPaBnliPLPl1RzLDE0BiWbpjkGEycCO++C7XZueVDRERkpyxbW4t7/ENjJIwa2JPOBXmUdZBOJ0QkMxas3JB2aIxk44ftRs8uhVmMKjeUKGZYZSUMHpy97U2cCFu2hE5tREREWqulNeGMZv9e2UkUC/Pz2HdwUYdoHiYimTNvxXp279O90TIVqzdw6/MfbTuutVexNT01s1LgAWAAUA9McffbUsqcDVwZvVwHXOzu70bz5gNrCWNE1bn7+LhizaQf/xjysph+T5oEzz4L++2XvW2KiIi01NDdunPLl8ayz6DsDVtxzUmj6d5Zd9mISPNsqtvK4jUbG+zxNGH1+i3c9sLHjOjfg//Yf1CWosu+OI+edcB33f0dM+sJzDCz5919dlKZecDh7r7azE4ApgATk+Yf4e4rYowx4447Lrvb690bjj02u9sUERFpqZKenZv88ZVpBwxNP2C2iEg6W+ud7x83igl77NZoueSm7e05UYzt2pe7L3H3d6Lna4E5wOCUMv9y99XRy2lAdmuQDFu3Dp57DlauzO52Z86EX/86u9sUERFpidmLa7LeDHRrvfOn6YuYNjfLFbOItEndOhVw8aS9OGj3xk8yJZq2z2znTduz0kjSzIYBBwCNDeTwDeCZpNcOPGdmM8zswviiy5w5c8IVxddfz+52X3gBLrsMli3L7nZFRESa6/aXy7nssbKsbjPP4MZ/fMDj0xdldbsi0jYtXrORyjUbmzX+6rjSYt6vrG50zMW2LvZE0cx6AH8GvuPuNQ2UOYKQKF6ZNPkQdz8QOAH4f2b2+QaWvdDMppvZ9OXLl2c4+paprAx/s9mZDYQObUDjKYqISOu1tLqW/r06Z3WbZsa40mL1fCoizXL7S+WceNurjfZ4mjCutJj8PGPhqg1ZiCw3Yk0UzayQkCQ+5O5PNlBmf+Au4FR339Y2xN0XR3+XAU8BE9It7+5T3H28u48vKSnJ9FtokYqK8HdIlhvQHnRQGFNRiaKIiLRWS6prGVjUNevbPWBob+auWN/g4NkiIgkLVm5gWN/GezxNOG6fAfz7uuPYq6RHzFHlTmyJooVU/G5gjrvf0kCZocCTwLnu/lHS9O5RBziYWXfgWOD9uGLNlMpKKCyEbOer3bqFXk+VKIqISGtUX+8sW1ubtaExko0rLQagrEJXFUWkcfNWrGdYn27NKtupII/8vCwNnJ4jLUoUzax3dAWwOQ4BzgWONLOy6HGimV1kZhdFZa4F+gB3RPOnR9P7A6+Z2bvAW8Df3f0fLYk1FyoqYNCg7A6PkXDwwTBrFjSjSbWIiEhWrVy/mS1bnYFF2U8U9x9ShBl8vHRt1rctIm1H7ZatLK7eyLAmxlBM9vCbC7nowRkxRpVbTQ6PYWYvA6dEZcuA5Wb2irtf3thy7v4a0Gia7e7nA+enmT4XGNtUbK3ND38IS5fmZts33AC//S00o0m1iIhIVvXsUsDDF0xschDreLZdyIxrjmG37p2yvm0RaTsWrdqAO+zRzKanAKs3bOYfs6qo3rCFom6FMUaXG8259lUUdULzn8C97n4QcHS8YbVNo0bB4YfnZtvFxVCgMYVFRKQV6lKYz+f26svg4uzfowgoSRSRJvXr2YXbJo9rcgzFZO29aXtzEsUCMxsIfAn4W8zxtFnucO+98MEHuYvhhz+Em2/O3fZFRETSmb24hr+9tzhn3cjPWVLDxX+cwaJ23DuhiOyaom6FnDpuMINacEIr0bS9vfas3JxE8SfAs0C5u79tZnsCH8cbVtuzZg18/eswdWruYnjrLXjkkdxtX0REJJ2//3sx3360jLwc3R/hDs+8X8U7C1fnZPsi0vq9s3A17y5qWcLXs0shI/r1oGxR+zy2NJoomlk+UOru+7v7JRDuH3T3L2YlujYkV0NjJJs4Ed57DzbohKmIiLQiS6pr6d+zc856CBzZvwddC/OZ2U7P+ovIrvvVcx/y46dntXi5o0f3Z2COmtXHrdFE0d23EjqykSZUVoa/uU4Ut26Fd97JXQwiIiKpltbUMiAHPZ4mFOTnsd+QIspaeLVARDqO+Ss2tKgjm4Qrjh/FL76wXwwR5V5zmp7+y8x+Z2aHmdmBiUfskbUxiSuKgwfnLoaJE8PfadNyF4OIiEiqJdW5TRQBDigtZvbiGjbVbc1pHCLS+iSGxti9mWMoppOre7Dj1Jx+Mj8X/b0+aZoDR2Y+nLaroiIMTTFwYO5i6NcPDjlEQ2SIiEjr4e5UVdcyaWS/nMYxfthuvDF3JSvWbc5Z76si0jot3ImhMRLcnWNu/SeHDu/LdafsE0N0udNkoujuR2QjkLbu29+G006DTjnugfu113K7fRERkVRT/+swOhU0pxFTfI4Z059jxvTPaQwi0jrNX7EegGE7MdarmbFb907tsml7k0dtMysys1vMbHr0+JWZFWUjuLakd28YNy7XUXzKPdcRiIiIhB9Rw/p2b1GX83FyVZAikuKze/Xh8W9+lpH9e+7U8u21aXtzTu/dA6wljKP4JaAGuDfOoNqiO+6A//u/XEcBH38Me+wBf/lLriMREekYzOzPZnaSmeX2klkrVb5sHX/451xWrd+c61D41XMfcuJv1PRGRLbXs0shE/bYja6d8ndq+XGlxWzeWs+cJWszHFluNadS28vdfxwNizHX3X8C7Bl3YG3NNdfAU0/lOorQ62pFBbz5Zq4jERHpMH4PnAV8bGa/NLNRzVnIzI43sw/NrNzMrkozv7OZPRbNf9PMhqXMH2pm68zse5l4E3F5Z8Fqfj51Dus31eU6FLp1KmDOkppWkbSKSOvx5DsVvF6+YqeXHze0GICydjZWa3MSxY1mdmjihZkdAmyML6S2Z8MGWL06t0NjJHTtCmPHKlEUEckWd/8/dz8bOBCYDzxvZv8ys6+ZWWG6ZaJxim8HTgDGAF82szEpxb4BrHb34cCtwI0p828FnsncO4nHkupaAPr16pzjSMJZf6DFg2qLSPt287Mf8ucZFTu9/MCirlx0+F6MGdS+7s5rTqJ4MXC7mc03swXA74CL4g2rbUmMoZjLoTGSHXwwTJ8exlQUEZH4mVkf4DzgfGAmcBshcXy+gUUmAOVRS53NwKPAqSllTgXuj54/ARxlFvq1NrPTgLlAy0eHzrKqmlr6dO9E54Kda9KVSfsPKSLPYKYSRRGJ1G7ZypLqWnbfiY5skl11wigm7LFbhqJqHZpMFN29zN3HAvsD+7n7Ae7+bvyhtR2JMRRbwxVFCOMprlsHs2fnOhIRkfbPzJ4EXgW6ASe7+ynu/pi7fwvo0cBig4FFSa8romlpy7h7HVAN9DGz7sCVwE8y9y7iU1W9MedjKCZ071zAyP49mdnOmoeJyM5bsHIDAMP67vwYigB1W+uZvbimVTSzz5QGh8cws8sbmA6Au98SU0xtTmu7onjoofDNb0Ln3LfyERHpCO5y96nJE8yss7tvcvfxDSyTbsTb1O44GyrzE+BWd19njQyca2YXAhcCDB06tMFycauq2cSgVpIoAnx5wtB2OTC2iOycedHQGDszhmKy6QtWM3nKNO45bzxHjmofQ/E0No7izvUP2wGddRYccwz06ZPrSII99oD/+Z9cRyEi0mH8DJiaMu0NQtPThlQApUmvhwCLGyhTYWYFQBGwCpgInG5mNwHFQL2Z1br775IXdvcpwBSA8ePH52xMiKcu+RwbNreeeyG++rlhuQ5BRFqRBStDorirTU/3GxyatpctXNP+E8Wod1Nphrw86N/KPg9bt8LcuTBiRK4jERFpn8xsAKF5aFczO4BPrwD2IjRDbczbwAgz2wOoBCYTek5N9jTwVULSeTrwoodBAA9LiuE6YF1qktiadCnMp0th7u9PTFa9cQub6rbSr2frudIpIrlx/mF7ctL+AynqmrbvsWbb1rS9Hd0D3eQ9imY2xMyeMrNlZrY0Gi+qldyN1zrccUfru4L3i1/AqFHhXkUREYnFccB/E64G3gL8KnpcDlzd2ILRPYeXAs8Cc4DH3X2WmV1vZqdExe4m3JNYHq1zhyE0WrtlNbVc/9fZfLS09YwtVl/vHPrLF/ntC+W5DkVEWoH8PGNI7127PzHhgKHFvLtoDfX1OWvEkVHN6fX0XsJZzUGEM6d/jaZJ5L77Wt8A9+PHQ3196P1UREQyz93vd/cjgPPc/Yikxynu/mQzlp/q7iPdfS93/3k07Vp3fzp6XuvuZ7j7cHef0vXQ7AAAIABJREFU4O5z06zjOnf/74y/uQyZu2I997w+j2U1m3IdyjZ5eca+g4soa0dn/UVk590wdQ4vfbgsI+s6oLQ3NbV1zIuas7Z1zUkUS9z9Xnevix73ASUxx9WmVFa2no5sEiZMCH81nqKISDzM7Jzo6TAzuzz1kdPgWomlNWEMxQFFrat3tQOGFjNnSQ21W1rPvZMikn0bN2/lzn/O5f2K6oysb9LeJdz3tc8wsBV14LUrmpMorjCzc8wsP3qcA6yMO7C2YssWWLKk9QyNkdCnDwwfDtOm5ToSEZF2K9HzQQ9CB3Cpjw5vSXUiUeya40i2N660mLp65/3KzPw4FJG2aX505W/YLvZ4mtCvVxcm7d2Pbp0a6y+07WjOu/g68DvgVkK33P+KpglQVQXure+KIoTxFF98McTXSA/qIiKyE9z9zuivOn9rQFV1LT06F9Cjc+v60TRuaDEAZYvWMH5Y+xogW0Sab36GhsZI9u+KamYtrmbyhNwNS5QpTV5RdPeF0f0WJe7ez91Pc/cFTS1nZqVm9pKZzTGzWWb27TRlzMx+Y2blZvaemR2YNO+rZvZx9Phqy99adixbBoWFre+KIsC3vgV/+ENIFEVEJB5mdpOZ9TKzQjN7wcxWJDVL7dBqarcwoBU2werXsws3n74/R49uZV2Wi0hWzV+5AYDd+2SmMxuAZ95fwjV/eb9dNG1v8BRfND7TXHf/n5TplwED3P3KJtZdB3zX3d8xs57ADDN73t1nJ5U5ARgRPSYCvwcmmtluwI+B8YSrmDPM7Gl3X93C9xe7gw6C2trWmYxNnJjrCEREOoRj3f0KM/sCYezDM4CXgD/mNqzcu+VL41rt4PZnjC9tupCItGtrNmymX8/O9Oyya0NjJEs0bZ+1uJqDdm/bLRYau6L4H0QD9aa4DTipqRW7+xJ3fyd6vpbQ/XdqA81TgQc8mAYUm9lAQpfjz7v7qig5fB44vsl3kyN5eZDfuoaI+v/s3Xd4XMXV+PHvqMuqlmxLLrLcu0GuK9M7hhSHlgChhAAOIaS+8AsEAoEQEkiANFJ4KSaEF0iAEAgQCIZQbLzuvRdZlmxZVrFkSVaf3x+zC2t1ydqde3fP53n0SNp7pTkrrbR77syc86mPPjLLT4UQQgSN/xXGhcDzWusKm8E4TWx0T8ohhF5lbSP/XFvM4bpG26EIISy548LJLL39rH79nv6l7WsK3V9Zuav/3lpr3e4yoO+2Xu14U0qNAmYAbWtwDgf2BXxe5Luts9sd58kn4ZZbbEfRudtug3vusR2Fe918M0yY8Nlbua+M069/fezt/rd6U7eBn/2s/bFJkz77vj/6UfvjM2bAvn3tYxAiVJ54ouPH9aFD5vhvftPx8TqzcocHHmh/bOLEz77/nXfCtY7dSHBcXldKbcWsglmslBoM1FuOybrmllZufm4V72/tn7Lz/W3noRq++8Jalu+RvF6ISBbTzxezhqQkMDw9kTVh0IKnq93ldUqp8VrrHYE3KqXGA0d7OoBSKhl4Gfie1rq67eEOvkR3cXtH338hsBBg5MjQbxpdvBiWLw/5sD3m8Zh9ik1NZi+l6Ln6evPCecoU8wYQ4/uLGT7c9KpsK8r3vyYnp/3xwIJCo0Yde7yqCs4+G1KkTqKwYP16GD8esrM7flz7/3cMG3Z8j/vcXEjqv3oBjqG1vl0p9SBQrbVuUUrVYlbMRLSymkbe3FDCSWMH2Q6lQ9OHpxEdpVi77zDnTc22HY4QIsTqGpu5+bnVfP3k0Zw2oX87/+XlmBY8btdVong38JZS6n5gle+22cAdwPd68s2VUrGYJPG5TpoPFwGBmwRGAPt9t5/R5vb/djSG1vpxfEtkZ8+eHfKdgkVFzixk45efD7/9LWzcaGasRM+tWWMS7HvugYsuOvbYZZeZt85cc41568zCheZNCNuamswFpW9+Ex55BD7/+c7P7e5xf/XV5q0zYf6Yn4zppxj4vPoXW8E4wYEqc03Zqf3EEmKjmTw0hXVF7r/qL4TovYKyOv677RCXzur/F/L3LZhKaqL7Z2g6nWvVWr8FfAk4E1jkezsDuERr/WZ331gppYAngS1a60c6Oe014Bpf9dN8oEprfQB4GzhPKTVQKTUQOM93m+MUFzuzNYafv6CNt+2iX9GtGTNgyRI488zQjLdtGzz3XGjGEsJv/Xozey7Fr/pOKfUs8CvgFGCO762DudfIcrDarL7NSnVmogjmqv/6fVW0tjqwIp0QIqg+7aGY2f9LXTKT4x27P7s3umxspLXeCPR1R8nJwNXABqXUWt9tPwJG+r73n4A3MZv/dwJ1wHW+YxVKqZ8CK3xfd58TiwNobRJFJ88ojh4NgwaZ5bE33WQ7GndJSICTTgrdeC+8APfeC1/4AqSmhm5cEdn8F5Hy8+3G4XKzgSlaO7H+tT0Hqkyi6NQZRYC8nIH8dVkhu8tqGDdE1v4LEUk+TRT7sYein9aaB97cwuhByVzpcW8/xaB1wNVaf0w3RW98T6rf6uTYU8BTQQit3xw5YvbsjB5tO5LOKWVmxXJzbUfiPg88AGedFboX0B6PufiwcqUZV4hQWLYMsrLAwhbvcLIRyAYO2A7ESVo1ZKcmkJEUZzuUTp03NYulY89ydDIrhAiOgrJaBqfEkxzf/+mQUopPdpezaX+1JIqRKjUVdu+2HUX3JkywHYH7HDpkKjT+8pehSxTnzjXvvV5JFEXoeL3mIoXqVS1r0cYgYLNSajnQ4L9Ra/1FeyHZd/0po7n+FAdfSQVSE2JJ7cf+aUII90iMjWamr5VFMOTlpPPqmv20tGqio9z5JCuJYgQoLYUHH4TLL4c5c2xH4w7+5Xih3LeVkWEqTy5bFroxhXjySamI3A9+YjsA0XdvbyphdWEld1ww2XYoQogQunfBtKB+f//S9l2HapiQ5c6l7d3uslRKjVZKPaKUekUp9Zr/LRTBOd1LL8H558NhhxdMi4sz1Qzfecd2JO7h9UJ0NMyaFdpxPR5YsaL784ToL6ecIoVsjpfW+gOgAIj1fbwCWG01KAf45l9X8cRHzl92s7G4iv/9cDd1jc22QxFChJG8HDNbubbQ4YlCF3pSjudVzBPg74CHA94i3rp18O67kJxsO5KupaebZu9S+bTnvF6YPh0GDAjtuL/4BWzZEtoxReR67z14/XXbUbifUupG4CXgz76bhmOeOyOW1prFW0spPdLQ/cmW5eWk06phQ1GV7VCEECGytaSa+b/+kFV7g1crc8ygJMYNSaahpTVoYwRbT5ae1mutfxv0SFyouBiGDv2sCbuTeTzw1lumWIrsReqa1rBrF5x7bujHdnKrFRF+Hn4Y9u41lXbFcfkWMBfwAmitdyilhtgNya7DdU00NreS7eDWGH6fXvXfdxjPmEzL0QghQmFXaS1bS46QEBsdtDGiohTv/uD0oH3/UOjJjOJvlFL3KKXmKaVm+t+CHpkLFBW554W9x2P2KhYU2I7E+ZSCnTvNi2gbHnzQ7BsTIpi0/qyQjThuDVrrRv8nSqkYIKJbZfhbY2S7oJpoZnI8ORmJrHHx8jAhRO8Es4diOOlJojgduBH4BZ8tO/1VMINyi6IiZ/dQDJSfD4MHw759tiNxB6UgydL/jn/+E55+2s7YInLs3g3l5ZIo9pMPlFI/AhKVUucCfwcielFvSfVRwB2JIsDs3AyONrXYDkMIESIFZbUMSYknKQitMQJt2l/FaQ+9j3d3eVDHCZae/HQuAsYEXi0VxpgxMGOG7Sh6Ji8PDh6UZac98bOfmdnX3/zGzvj5+fDHP0JTk1SjFMFjo7JvGLsduB7YAHwDeBN4wmpElkVHRTFteCrD0hJth9Ijj3z5RJQ8QQoRMQrKa0Mym5idmkBhRZ1rl7b3JFFcB6QDpUGOxXX+9S/bEfScPP/13EsvQabFv2WPBx59FDZsgJmyyFsEyerVpljT1Km2I3E/rXWrUupV4FWt9SHb8TjB6RMGc/qEwbbD6DFJEoWILFOGpjI4JT7o42QmxzMyYwBr97lzaXtPlp5mAVuVUm9Lewx3e/55U8mzUeaGO1VXZxI0m7Ms/rGlSq0IpoceMhV23VCMy6mU8ROlVBmwFdimlDqklLrbdmyid7TWXPf0cn67eIftUIQQIXDvgmncctb4kIyVl5Pu2j3QPUkU78EsP30AaY/xqQ8+gClTYP1625H0XEwMbNxo2nqIjq1aBS0tdhPF3FwYO9b5/TmFu0VFwciRtqNwve8BJwNztNaZWusMwAOcrJT6vt3Q7Pr+i2u59e/uebJRSlFR18SSnWW2QxFCBFlrq0br0NUby8tJp6S6nhJfkS836TZR1Fp/0NFbKIJzsj17zNV4WwVP+kJmqrrnhH1bSsGOHXDHHfZiEOFtwwa44QapgtwPrgGu0Frv8d+gtd4NXOU7FrE27a/iSH2T7TB6ZUZOOhuKq2hpjeiCtUKEvTc3HuDEe99hT1ltSMabNzaTK+bm0Nzqvn6K3SaKSqkjSqlq31u9UqpFKVUdiuCcrLjYvB82zG4cvZGTA9nZkih2JTERzj4bsrLsxiHbZUQwvf++acEixZKOW6zWut0UlG+fYkT/dEuq6l3RQzFQXk46dY0tbD94xHYoQogg2lteR3V9M1mpwd+jCDB5aCo/v/gERgwcEJLx+lNPZhRTtNapvrcE4BLg98EPzdmKikzBk0R3FHQDTPLh8Uii2JVvfQvefdd2FLB9O8yeDYsX245EhCOv1/SAdUsfWAfrasd3t7vBlVLzlVLblFI7lVK3d3A8Xin1ou+4Vyk1ynf7XKXUWt/bOqXURX2+B0FQ29BMdX0z2S6peOqXl5MO4NqiE0KIntlTVktWajwD4kK3Sb+1VVN8+GjIxusvPdmjeAyt9avAWUGIxVWKi935ImvBAjjtNLMPTxyrpcU0IXeCrCxTlXLpUtuRiHDk9UpbjH5yYsCKm8C3I5gexJ1SSkUDjwEXAFOAK5RSU9qcdj1QqbUeBzwKPOi7fSMwW2udB8wH/qyUckxZopJqsw8nOy00V+v7S27mAM6bkkVGUpztUIQQQVRQVktuCFpjBHrgzS2c8/AHNLe4a/lpt08sSqmLAz6NAmYDDnk5bc+JJ5piNm5z3XXmTbT3+uuwcCF8+CFMmmQ3lrQ0E4PM/or+VlYGu3aZx7o4Plrr6OP48rnATt+eRpRSLwALgM0B5ywAfuL7+CXg90oppbWuCzgnAQc+J58zOYuxg5Nth9ErSikev2a27TCEEEFWUF7L2ZNCu8do2vA0jja1sP1gDVOGpYZ07OPRkyuQXwj4uBkowDx5RbSf/tR2BH2nNVRVQXq67Uicxes1lUZHjbIdieHxmF6dWsueRdF/ioth3DjIz7cdScQbDuwL+LwIUzG1w3O01s1KqSogEyhTSnmAp4Bc4GqtdXPwQ+6ZsYOTeeJa9yZctQ3NxEZHERfT60VXQgiHa23VXDorhxkjQ/siOHBpe1glilprmX9qw+0v3E89FVJT4c03bUfiLF6vmSlOcEj9BY8HFi0yFXbHjLEdjQgXJ55oquoK6zp6Fmk7M9jpOVprLzBVKTUZeEYp9ZbW+pja60qphcBCgJEh7IWitXZtA/vleyq4/PFP+Ov1Hk4aN8h2OEKIfhYVpbj9gtAvG8vNHMDAAbGs3VfJlR739Kbq9HKZUuruLt5+HMognaagwCRaL71kO5K+8S9pdMp+PCdoaYEVK5y1b+vUU+HSS6Gx25IYQggXKgJyAj4fAezv7BzfHsQ0oCLwBK31FqAWmNZ2AK3141rr2Vrr2YMHD+7H0Lt27+ubOe9Rd3bRmpCVTKuGNVLQRoiwVF3fRG1D6BdgKKU4MSfddcWyulpXUdvBG5jN9T8MclyOVlwMR45ASortSPrG44GKCti503YkzrFlC9TUOCtRnDoV/v53+/slRfhobYXJk+Gxx2xHIoAVwHil1GilVBxwOfBam3NeA671fXwp8J7WWvu+JgZAKZULTMRsC3GE4sNHiXLpjGL6gDhGD0piTaG7XswJIXrmmSUFTPvJ29Q3hb6q48JTx/DD+e56Udfp0lOt9cP+j5VSKcB3geuAF4CHO/u6SFBUZN6PGGE3jr7yJ0NeL4wfbzcWp0hKgv/5HzOL5zQVFZCRYTsKEQ527ICtW52zvDqS+fYc3gK8DUQDT2mtNyml7gNWaq1fA54EnlVK7cTMJF7u+/JTgNuVUk1AK3BzR/0cbSmpqic7zb0PsrycdD7aUebqJbRCiI7tKa8lKyWBhNjjqUXWN25czt7lTm2lVIZS6n5gPSapnKm1/qHWujQk0TlUcbF578b2GGBmqpKSpKJmoNGj4Ve/ck4hG7/77oOhQ6GhwXYkIhz4/+alkI0zaK3f1FpP0FqP1Vr/zHfb3b4kEa11vdb6Mq31OK31XH+FVK31s1rrqVrrPK31TF/bKscoqa4nO9XdiWJZTYMre54JIbpWUFbLqEH2Gt8v31PB6sJKa+P3Vld7FH+JWRpzBJiutf6J1rrH90wp9ZRSqlQptbGT47cFNAzeqJRqUUpl+I4VKKU2+I6t7OV9CrqiIpNopaXZjqRvoqPh4YfN/jdhrFvnzGRsyhSzR3HdOtuRiHCwbJlZMi/LmUWwNLW0UlbT4OoZxdMnDObuz08JaTNuIURoFJTXMXpQaHsoBrr95fX88b+7rI3fW13NKP4PMAy4C9gf2EhYKVXdg++9CNMIuENa61/6robmAXcAH2itAzfpn+k77rga23PmwE03ubvy6Te+AaefbjsKZ6ipgZkz4YEHbEfSXuAyYSGOl9dr/n9Fh37FjYgQjc2tXJ2fy6zcgbZD6bNRg5L4+imjyUiKsx2KEKIfVR1toqK2kdxMe4liXk46awoPo11SUbLTRFFrHaW1TtRap2itUwPeUrTW3TYA0Vp/SJvqbF24Ani+h+dad+WVZpmimzU2wscff7aMNpKtXGmKfDipkI3fiBFm6akkiqI/nH02fOUrtqMQ4SwpPob7Fkzj1PGhq7IaDAer61my0zHbPoUQ/SBKwb1fnMppFv8/5Y1019J2691klVIDMDOPLwfcrIF3lFKrfH2gHOXIEfe3ligrM4Vb3Nrioz/5kzAnJopKmf1kkiiK/vDQQ7DQcf9RRTipb2qhqaXVdhjH7fEPd/P1RSvC4r4IIYyUhFiuPWmU1Yb3eTnpAK5pk2E9UQS+ACxps+z0ZK31TOAC4FtKqdM6+2Kl1EKl1Eql1MpDhw4FO1ZaWkwFynvuCfpQQTVsmJmtkgTE7NsaNw4yM21H0rGbboIf/9j9FyeEXYcOSU9OEXx/XbaXCXe9RVVdk+1QjkteTjoNza1sKzliOxQhRD/ZU1bLrkM1VmOYlJ1KfEwUa13SgscJieLltFl2qrXe73tfCvwDmNvZF4e6oXBpKTQ3Q3Z20IcKOo/HJEmRTGuTLDtxNtHvvPPgmmvcvSdW2HfLLTB9uu0oRLgrqaonPiaK1ER3F4LxX/Vf45Kr/kKI7v1u8Q6ufsLuDElcTBSv3XIKt54/0WocPWU1UVRKpQGnA/8MuC3J17cRpVQScB7QYeVUG/x7+tzaQzGQxwN79piZhkj2/PPw/e/bjqJrGzbAqlW2oxBu5vXCiSfajkKEu5LqeoamJbq+/+CIgYkMSo5zzVV/IUT39pTXWi1k4zcxO8VKH8e+CFqiqJR6HvgEmKiUKlJKXa+UukkpdVPAaRcB72itawNuywI+VkqtA5YDb2it/x2sOHurqMi8d2sPxUBSUdPM0p1+OsyaZTuSrn31q3DXXbajEG518CDs3Sv9E0XwlVTVk5UabzuM46aUIi8nnbX73NPvTAjRNdND0X6ieKDqKA+8uYWdpXaXwfZE0NaGaK2v6ME5izBtNAJv2w049rp3OM0ozpljKp/OnGk7EnveftssP53faSMXZ/B44OWXTawuv1AvLHBywSYRXkqq65kzKsN2GP3ih/MnER/jjqv+QoiuVdU1UVnXxOhBA2yHQnOL5vEPd5MzMJFxQ5Jth9MlJ+xRdJWZM+H22yEE2yGDLjERTj7ZvI9UP/sZ3Huv7Si65/FAZSXs2GE7EuFGXi/ExET2RSERGl87aRQXTh9qO4x+MT4rhZGZ9l9UCiGOX0G5Wbw4ygFLT/1L292wB9rdu80tmDfPvIWLNWvMTNV990FUhF02aG42+/5uvNF2JN0LXCY8YYLdWIT7XHIJjB4d2ReFRGjccOoY2yH0G601z3kLGZISz3lTw6CCnRARbFRmEo9fPYtZuQNthxKwtN35iWKEpQbHr6AAqqttR9F/1q41s2rbttmOJPQ2boS6Oncsx5syBZKTI3s/qei7mTPhhhtsRyHCXW1DM0WVdTSHSe9BpRSLlhbw/PJC26EIIY5T2oBYzpuaTWayM/ZQ5+Wks/tQreNbCUmi2EvnneeOGaieiuSCNm7atxUdDe++a2Z+heiNAwfgzTehtrb7c4U4Hkt3lXPKg++zaX/4XE31X/XX0shWCFdbsrOMlQUV3Z8YInk5Axk4IJZ9lXW2Q+mSJIq9oLUpZhMOhWz8Jk2C1NTITBRXr4ZBg8ySPDfweCAjPGpEiBB66y343Odg3z7bkYhwV1JdD8DQtATLkfSfvJx0KuuaKKxw9os5IUTXfvn2Nh75z3bbYXzqpLGZrP7xuUwbnmY7lC5JotgLhw+bpYrh0BrDLyoK5s6NzETxj380yaJbqogeOgQPPACbN9uORLjJsmWQliZ7W0XwlVQdJTpKOWZpV3+YMTIdwBV7iYQQnSsod0ZrDL+oKOWKfrOSKPaCv4diOM0ogpmpKiqCJmcvk+53UVGQk2M7ip5rboY77zQtPYToKa/XXAyKtGJVIvQOVNWTlRJPdJTzX/z01MSsFJLioikslxlFIdzqcF0jh+uaGO2AiqeB/rZiHxf/YYmjl7bLS4de8PdQDKcZRTDJR0kJxMbajiR0vF74xjdg/37bkfTc0KEmsY3E2V/RNzU1pmiTG/bhCvc7WF1PVhgtOwWIiY5i5V3n8u2zx9sORQjRRwW+Cz1OmlEEaGptZXXhYUcvbZdEsRcmT4bHHjP7+sJJYmLkzTa8+y48/jgMcFmLLI9HEkXRc6tWQWurJIoiNL5+8mi+cdpY22H0u8S4aNshCCGOQ0GZqeY2epCzXvTl5Th/aXuEpQfHJzcXbr4ZMjNtR9L/7rwTbrvNdhSh4/WahD893XYkvZOfb1q0lJbajkS4wSmnwPr1cMYZtiMRkeDsyVnMnxZ+/QZ3lh7h2qeWs7G4ynYoQog+OG9qFq/fcgq5Dlt6OjErhcTYaNYUSqIYFjZtgq1bbUcRHLt2wd/+ZjuK0NDaJIpunGXxeCA+PjL7Xorei46G6dNND04hgqm+qYUVBRWO7wnWF0nxMXyw/ZCjSusLIXpuQFwM00ekERvtrLQnJjqK6SPSZEYxXNx6K1x1le0ogsPjgcJC03Mt3O3da2bk3Jgo5udDdTWceqrtSIQb/PCH8OGHtqMQkaCwoo7L/vQJH+w4ZDuUfjc0LZGs1HhHv5gTQnTu2U8K+GC7M/83nTcli8lDU22H0SlJFHuhuDj8Ctn4+ZOmSNj/duAAjBnjzkQxJgbi4mxHIdyguBgeegjWrrUdiYgEJVWmh2J2angVs/HLy0mXRFEIl/rVO9t5Z1OJ7TA6dMOpY/j5xdNth9EpSRR7oago/Fpj+M2YYZKQSEgU580zS21nzrQdSd+89BKcc44pUiJEZ/x/y268ICLcx58oDg2zqqd+eTkDKSivo6K20XYoQoheqKxtpOpoE6MdVvE0kNaa2oZm22F0SBLFHqqrg8rK8J1RTEyEL33JNOYWzlZTA4sXyz5F0TWv18w+5+XZjkREgpJqkygOSY23HElwzBk1EM/oDCrrJFEUwk0Kyk3F01EOK2QT6ILffMSd/9hgO4wOSaLYQ/4eiuE6owjw97/D7bfbjiK4Ghth7Fh4+mnbkfSdf4Zo2TK7cQhn83pNkhgfnq/bhcMcqKonMymO+JjwbCUxe1QGL35jHmMHS2UoIdzk00TRwTOKuZkDHLu0XRLFHsrOhn/+E846y3YkwaU1NDtz9rtfrF8Pu3dDknP/X3Rr4kQz8xsJy4RF32gNhw7JslOnU0rNV0ptU0rtVEq1u0ynlIpXSr3oO+5VSo3y3X6uUmqVUmqD7731Z6ZrT8rlV5edaDuMoGtukTX/QrjJvoqjRCnIyUi0HUqnnLy0XRLFHkpJgS9+MbxnFPfvh6wsWLTIdiTB40+u8vPtxnE8oqJg7lxJFEXnlDLtfB5+2HYkojNKqWjgMeACYApwhVJqSpvTrgcqtdbjgEeBB323lwFf0FpPB64Fng1N1J2blJ3KmZOG2A4jqH63eAf5P38PrbXtUIQQPfTts8ax8q5zHb3aIS/HNPVe58BZRUkUe2j9enjrLXOlPlxlZ5vZxHBOQJYtM/czJ8d2JMdn/nyzhDacH4/i+MXG2o5AdGEusFNrvVtr3Qi8ACxoc84C4Bnfxy8BZyullNZ6jdZ6v+/2TUCCUsrqIuO3NhxgT1mtzRCCbnBKPGU1DWF/P4UIJ0opMpKcXS7+hBFpRClYI4miez3xBFxxhblSH64iYabK6zXL8dz+e/zBD0z1U7ffDxEcd9wBCxfajkJ0YziwL+DzIt9tHZ6jtW4GqoDMNudcAqzRWje0HUAptVAptVIptfLQoeD1EKtvauGbz63mX+v2d3+yi+WNNFf9nbqXSAhxLK01t7+8nve3ltoOpUtJ8THcfsEkThk3yHYo7Uii2EPh3BojkMdjlqzV1NiOpP+1tsKFF8Ill9iOpP80NdmOQDjR66+b/1nC0Tq6zNN2jUCX5yilpmKWo36jowG01o9rrWdrrWcPHjy4z4F256Cv4ml2mLbG8Bs/JIWkuGhJFIVwicq6Jl5YsY9dh5z/onbhaWOZOzrDdhjtSKLYQ0VF4duWQ00SAAAgAElEQVQaI1B+vkmoVq60HUn/i4qCX/8arr7adiT94+yz4corbUchnKa6GjZvlkI2LlAEBC6CHwG0nZL79BylVAyQBlT4Ph8B/AO4Rmu9K+jRdsHfQzHcE8XoKMUJI9JZUyiJohBu4F8m7uQein6Nza2s2lvpuII2QUsUlVJPKaVKlVIbOzl+hlKqSim11vd2d8CxLivB2VBcHDkzij/4gSlqE25KS8NrBm7IEGmRIdpbscLsXZVE0fFWAOOVUqOVUnHA5cBrbc55DVOsBuBS4D2ttVZKpQNvAHdorZeELOJO+HsoDg3zRBHg8rk5fGlGBFw1FiIM7HVBawy/PWW1XPLHpY5bJhvMGcVFwPxuzvlIa53ne7sPelwJLqSamuDAgciYUczIMJUSJ0+2HUn/+9rXYN4821H0H4/HzHTvD+9tQaKX/HuM5861G4fomm/P4S3A28AW4G9a601KqfuUUl/0nfYkkKmU2gn8APBfOL0FGAf8OOBiq7WSo/4ZxazU8E8UF+QN5/pTRtsOQwjRAwVltaY1xsABtkPp1rghyY5c2h4TrG+stf7Q3/Oplz6tBAeglPJXgtvcf9H1TlQUrFplkqhI0NgIGzbArFm2I+k/WsPy5fClL9mOpP/4Z4y8XrjoIruxCOcYPNjsw42U/1duprV+E3izzW13B3xcD1zWwdfdD9wf9AB76NJZI5gxciApCZFRZrf0SD31ja2MzHT+i89QqG9qoa6xpd3taYmxREcpjja2cLSp/fH0xFiiohR1jc3UN7XvT+mvVFnb0ExDcyupCTHERMuOKdFzR5taGDM4mbgY5z9u/EvbIyZR7KF5Sql1mH0Zt2qtN9FxJTiri6iio2HGDJsRhNaf/wzf+Q7s2xc+y2137YLy8vBajjdjhml/IImiCHTjjeZNiFDJTI4nM9lqd46QuuixpcwYmc7vr5xpOxRHePaTvfzszS3tbvf+6GyyUhP40we7+M3iHe2Ob7z3fJLjY3j0P9v534/2tDte8IvPAXD/G1t4fnkhc0dl8LebwmhZkAi6Oz83hR9d6J4+YudNzWJbyRG01iiHlLW3mSiuBnK11jVKqQuBV4Hx9KwS3KeUUguBhQAjR44MRpxs2gRLlpj2GCkpQRnCUQJnqsIlUfQvxwunRDEhAe6+G2bKaxXh09hoVkDE2L4EKCLKK6uLyE5L4KSxzivtHgx5Oc676m/D0l1lzB2Vwbyxmdz7xantjqckmH9EZ04a0mEfuzjf7OB5U7MZ0cXSwC+cOJSW1lb+trKINYWVzBg5sJ/ugYgETkm4euK6k523rN3aywmtdXXAx28qpf6glBpEzyrBBX6fx4HHAWbPnh2Uywbvvgvf+154tVXoyoknQlycSa7C5T57vZCUBFPbP5e52l132Y5AOMmrr8J118Hq1TBxou1oRKR46N/bOGX8oIhKFN/YcICymgYGRdBMaqDtB49w5f96uetzk7nh1DFMG57W6bl5Oenk5aR3enzOqAzmjOp8rfxJYwdxwoh03tpQwqKlBZIoih4pr2ngW/+3mm+fNZ6THdif0C2sLdpVSmUrX5qvlJrri6WcnlWCC6niYjN7Eyl7fuLjzbJG/yxcOLjqKnjsMbOMOJy0tsLWrWZZrRBer3lMjBljOxIRKZpbWjlU0xARFU/98kaapGdtBLfJeHpJAfExUVwyMzTLjpLjY/jynBzeWH+AUl+VXSG6UlBey7LdFTQ2t9//KnoumO0xngc+ASYqpYqUUtcrpW5SSt3kO+VSYKNvj+Jvgcu10WEluGDF2RP+Hooumr0+bh6P6aXY3Gw7kv4xdy5ce23357nNrl2mQu0rr9iORDiB12uWIsdGRk0R4QBlNY20tOqIqHjqN21YGtFRijX7Km2HYsXhukb+saaIi2YMZ2AHS0qD5bqTR/Gnq2ZF1H5Y0Xd7yuoAd7TGcLJgVj29opvjvwd+38mxdpXgbIqUHoqBFi4MnwqhhYWmAfnpp0Niou1o+te4cWam2+uVAiaRrqnJVGf+5jdtRyIiSST1UPRLjIvmj1+dyeShqbZDseLFFfuob2rl2pNGhXTcEQMHdLmXUYhABWW1REcpRgwMsxd+Ieb8erEO4J9RjCRTp8KZZ4ZHUYx//AMuuAAqKmxH0v+UMrOl4bRMWPTNhg1QXx9eBZuE85VUHQUio4dioPOmZpOTEZlJy8c7y8gfk2ElUa5vauGXb2/ljfUHQj62cJc95bWMGJhIrLRUOS5hkAYEn9drrtZHmsWLobra/a0Xli0ziX64JvseD7z9Nhw5EhlVeUXHMjPhJz+BU0+1HYmIJGdNyuKj/3cmQ1IjazlgZW0j/95UwukTBjMsPbJmLJ65bi6VdY1Wxo6PieKdTQf577ZDXDg921UVLUVoDUqKI390pu0wXE/S7B4YNAiGDrUdReg98gjceaftKI6f1xvesyz5+aC12VMqIlduLtxzDwwbZjsSEUniYqLIyRhAfEyYVQrrRnltA3e8soGPd5bZDiWkGppbiIpS1vYJKqX42smj2LS/mpV7I3OPqOiZexdM48FLT7AdhutJotiNvXtNr7o97XvBhr38fFNRs6rKdiR9d+iQ+d2Fc6J40kmmLcKMGbYjETZ9/LFZASBEKL2yuogXlhfaDiPkxgxKJiUhJqL6KW7eX83cny1m2W67ZbYvmjGc1IQYFi0psBqHEJFAEsVubNwIP/0plJbajiT0PB4zU7Vihe1I+s6/dy+cE8XUVFiwANI7b1MlwlxlpVly+rvf2Y5ERJoXV+zjldXFtsMIuagoRV5OekS1yHhmaQGNza1MzrZbxGdAXAxXzB3JvzeVsP/wUauxCGdatbeS03/5Pusi6EJOsEii2I2iIvM+0qqegimSAu4ulDJ/PqxZ89l9CVdbtsBvf2sSexF5li8378P5gohwppLqerIiqOJpoLycdLaWVFPXGCZ9pLpQUdvIq2uLuXjmcNIG2O+/c1V+LvOnZdPUIj3yRHu7D9Wwt7yOtET7j1W3k0SxG0VFEBUFWVm2Iwm99HSYOBHWrrUdSd/FxEBeXvi1xWhr8WL47ndh3z7bkQgbvF5TAXfOHNuRiEiiteZAVX1EtcYIlJeTTquGrSVHbIcSdM8vL6ShuZWvhbglRmdyMgbw2JUzyc2UHnmivYJy0xpjuLTGOG6SKHajuNgUsgmHNhF98f778MILtqPom9ZW+MEPTNXTcOefSXLz7K/oO68XJk2CtDTbkYhIcriuicbm1ohrjeF38rhBrP7xucwcOdB2KEHV3NLKX5ft5dTxgxif5azS2jtLj7CyIAx7X4njUlBWR460xugX8hPsxsGDkbns1G/oUIh2aTG77dvh0UfNssxwd+KJEB8viWIk0tr83vPzbUciIk3pkQaAiJ1RTIiNJiMpznYYQRcTHcUfvjqT286faDuUY2it+fbza7nr1Y1o2XchAuwpq2XUIJlt7g8ROk/Wc//6F9TW2o7CnsOH4Y474OKL4dxzbUfTO5FQyMYvLs5UPY2E2VPR3ttvQ0JkvlYXFk3MTmH7/RfYDsOqdzaV8M7mg/zqshNthxJUMxw4a6qU4msn5fLDlzewbHcF88ZKzzxheMZkMEqWJfcLmVHshlKQnGw7CnuSkmDRInjrLduR9J7XayqCTppkO5LQ8HhgwwZoabEdiQglpWDWLJg61XYkIhLFxUQRFxO5LyX2VR7lpVVFHKyutx1KUGwsruL2l9dTesSZ929B3nDSB8SyaGkE9jATnbrnC1O51iH7ad0ucv+790BNDVx3HXz0ke1I7ImNNS9C3bik0es1xT2iIuRRfvfdZqm0W5cKi7555RV4+WXbUYhI9Pq6/dz7+qaIXvaXl2P6Eq0J0zYZTy8p4PV1+0mIdeYTS0JsNFfMHcl/Nh9kX0Wd7XCEAzS1tNLaGrn/k/pbhLyE7puiIjObVhh5vYSP4fHA6tXQ2Gg7kp5rbja95SJh2alfRoYsP4xEDz1kWqMIEWof7yjjjfUHUErZDsWaqcNSiY1WrA3Dfm1lNQ28vm4/l84aQWqCc9sMXJ2fS1JcDBuLq2yHIhzgH2uKmXz3v6XHZj+RRLELkdxDMZDHA/X1sH697Uh6LiYGdu+Gn/zEdiSh9fOfw4MP2o5ChEpDg+kTGkkXRIRzHKiO3NYYfgmx0UwZmsqawkrbofS7//MW0tjSyjUOX8I3LD2R5XeewwXTh9oORThAQVktLa2aISnxtkMJC5IodqG42LwfPtxuHLZ5PJCbC+XltiPpvVjnXgQNiqVLzSy4iAzr1pmZfkkUhQ0lVUcjtjVGIM+YzLArw9/YbFpinD5hMGMHO79QQ2JcNFprKmtdtPRJBEVBeS05GQOICbO/SVuk6mkX/DOKkZ4o5uZCQYHtKHrnO98xexN//WvbkYSWx2Mq9R4+DOnptqMRwRZJlX2F85RU1TNvjFSa/NGFk22H0O+ONrUwf1o2503Jth1Kj9320nrW7TvMO98/LaKXQ0e6PWV1jMocYDuMsCHpdhcaGsyy08RE25GI3nr1VThwwHYUoefvpbdihd04RGhs3gzDhsnyeBF69U0txMVEMzRdniDDUVpiLPctmMYp4wfZDqXH8sdksqO0hqW7XLj8SfQLrTV7y6WHYn+SRLEL990nhWz8Xn7ZvBitqLAdSfcOHIB9+yJzlmXOHNMuwY1VakXv/eEPpiWKEKGWEBvNyrvO4RunjbEdiiNcv2gFd/9zo+0w+sXO0hqW76lwXTXbz58wlMykOJ5eIq0yIlVTi2bhaWM4a9IQ26GEDUkUuyGrF4yBA82ezeXLbUfSvUhejpeWBiefLL0UI4VSptqtELbIEj+jRWu8u11wJbUHfv/eDr6+aAV1je56IkmIjeZKz0gWby1lb3mt7XCEBXExUXzvnAmcOn6w7VDChiSKXbj0UikM4jd7tntmqrxeU/V05kzbkdjx0Udwzz22oxDB9uGHcOWVsH+/7UhEXyml5iultimldiqlbu/geLxS6kXfca9SapTv9kyl1PtKqRql1O9DHTfA+9tKWfiXlVRI8RDA9FPcXnqEmoZm26Ecl9Lqet7YcIDLZo8gKd59ZSyuys8lWin+b7ksB4tE5TUNlNU0uG423MkkUexEQ4NZbilLT43UVJgyxR2J4tChcPnlsrdUhLfFi+HFF83fpnAfpVQ08BhwATAFuEIpNaXNadcDlVrrccCjgL/5TT3wY+DWEIXbzub91byz+SCJDm3EHmp5OeloDeuL3N1P8TlvIc2tmmvnjbIdSp9kpSbwl6/P5fvnTLAdirDgiY/3kP/AYlpaJVHsL5IodsJfCCXSK54G8njM0lOnX6j5znfg2WdtR2HPvn0mqX/xRduRiGDyemHqVEh2fuV60bG5wE6t9W6tdSPwArCgzTkLgGd8H78EnK2UUlrrWq31x5iE0YqD1fWkJcaSGCeJIphEEWDtPvcmig3NLTznLeSsiUNcXQzkpHGDSJALGBGpoKyWkdIao18F7SeplHpKKVWqlOpwd7dS6qtKqfW+t6VKqRMDjhUopTYopdYqpVYGK8au+FtjSDXBz3zxi3DFFXD0qO1IOtfQIPvzhg417Uw++cR2JCJYWlvNRRt/lVvhSsOBfQGfF/lu6/AcrXUzUAX0uB+FUmqhUmqlUmrloUOHjjPcYx2oqmdomvRQ9EsfEMeVnpGMznRvgrWrtJZWrfnayaNsh3Lc3txwgK8vWkGrzCxFlD1lUvG0vwUz5V4EzO/i+B7gdK31CcBPgcfbHD9Ta52ntZ4dpPi6VFxs3suM4mcWLIDf/Q4GOLg9zV//avoH+hP9SBQTA7NmuWOZsOibHTugsjIyCzaFkY6qwLR9VduTczqltX5caz1baz178OD+Le5wsLqerFRJFAM9cNF0Lpg+1HYYfTZlWCpLbz+LU8a5pyVGZxqaW3hvaykf7SyzHYoIEdMao45RLr5Y40RBSxS11h8CnZYA01ov1VpX+j5dBjhq7k4pGD9eZhTbam52dvEMrxdiYyXB93hgzRpolDoTYamyEk44QWYUXa4IyAn4fATQ9r/rp+copWKANLp4Xg2ljKQ4JmWn2A7DcSprG6lrdF9Bm6q6JlpaNQmx0WFRyfbC6UMZlBzPImmVETFKjzRwtKmF0YMcPJvhQk5ZxHs98FbA5xp4Rym1Sim10EZAX/4ybN9uZqfEZz73ObjoIttRdM7rhblzpa2Jx2OW4a5bZzsSEQz5+eZ3O3Wq7UjEcVgBjFdKjVZKxQGXA6+1Oec14Frfx5cC72mHlPNbdN1c7rhwsu0wHGXz/mpm/PQ/vL+1f5f5hsKdr25gwWMfh021yPiYaK7KH8n72w6xp0xaZUSCxLhoHrrkBE4OgxlxJ7GeKCqlzsQkij8MuPlkrfVMTDW4bymlTuvi64O2B0O0l5cHa9eaJMRpampg40ZZjgdw0klw7bWQICvDwlKYvJaLaL49h7cAbwNbgL9prTcppe5TSn3Rd9qTQKZSaifwA+DTFhpKqQLgEeBrSqmiDiqmihAbNySZuJgo1u6r7P5kBzlQdZS3NpYwb0xmWMwm+l3pGUlstOKZpQW2QxEhkJoQy5fn5DBmsFR4609WE0Wl1AnAE8ACrXW5/3at9X7f+1LgH5jqcB0K1h6MK6+E227rt28XNjwes5xxzRrbkbS3apUp8iGJoll6u2gRTJ9uOxLR344ehSFD4IknbEcijpfW+k2t9QSt9Vit9c98t92ttX7N93G91voyrfU4rfVcrfXugK8dpbXO0Fona61HaK03hyruDUVVfOF3H7OhqCpUQ7pCXEwUU4elsqbQXZVPn1tWiNaaa1zaEqMzQ1IS+MG5E8Niz6Xo3pYD1WzaL/+T+pu1RFEpNRJ4Bbhaa7094PYkpVSK/2PgPKDDyqnBtGQJlJaGelTn8ydhTiyUMnw4/PjHkij6aQ1799qOQvS3NWugrAz6uTaJED1WWFHHhuIqYmPCZ/apv+TlpLOhuIqmllbbofRIfVML/7e8kHMmZ5GTEX57u755xljOmZJlOwwRAr9+dzvfed6BsxguF8z2GM8DnwATfctirldK3aSUusl3yt2YMt9/aNMGIwv4WCm1DlgOvKG1/new4uxIa6sp2BLpBVE6Mny4eXNiojhuHNx3H2T2uHh8eHv0URg1CsrLuz1VuIj/b08uiAhbDlSZHklDUxMtR+I8eTnpNDS3sq3kiO1QeuTtTSVU1DaGRUuMzhw60sATH+2WVhlhrqCsjtHSGqPfxQTrG2utr+jm+A3ADR3cvhs4sf1XhE5pqanuKRVPO/bIIzBsmO0o2vvwQ5gxA1KkEB8AM2ea98uXwwUX2I1F9B+vF0aOhOxs25GISHWwup6E2ChSE4P2EsK15o3N5OcXT3dNj8nPnzCMgQPimDcmfK+wfrK7nPvf2MKYwUmcNUlmF8NRa6tmb0Utp4yXZcb9zXoxGyfy9+CTGcWOffnLcMoptqM4VlERnH46PP207UicY/ZsiIpy5uyv6Ltly2Q2Udh1oKqeoWmJYVX4pL8MSUngirkjyUyOtx1Kj0RHKU6bMDisf5cXTMsmKzWep5cU2A5FBMnBI/XUN7UySmYU+50kih2IioKzzoKxY21H4kyNjfDOO6Z9iFMsW2beywvozyQnm/YJkiiGj5YWuOoq+MpXbEciIllu5gBOHhe+M1DHq6iyjn9vPGA7jG7d+Y8NPP7hLtthBF1sdBRXeXL5aEcZO0vdsSRY9I6/BcroTEkU+5skih2YORMWL4Zp02xH4kxNTXDhhfDss7Yj+YzXC3Fxpn2H+IzHY5aeSjuF8BAdDfffD5dcYjsSEcluO38S939JSip35tU1xdz019VUHW2yHUqnig8f5YUV+6iodW6M/elKz0jiYqJ4ZqlUeAtH04an8ez1c5k+Is12KGFHEkXRa0lJJol20kyV12v2J8a7Y7VPyNxwA/z5z2YmSrjf3r1QK72jhXC0vJyBAKwvcm6bjGc/2YvWmqvn5doOJSQyk+P5Ut4wquub0HLlNOykJsRy6vjBpCXG2g4l7Eii2IGbbjJLT0Xn/DNVrQ6oAN7cbHooyrLT9jweuPRSiJGaE2Hh+uvNXlwhbCmraWD2/e/y2rr9tkNxrBNy0lAK1jq0n+LRxhZeWFHI+VOzGZ4eOZVrf3HxCfzm8hlhvR8zUr29qYSlu8pshxGWJFHswPbt0NBgOwpn83igqsoZ+xSVgv/+F26+2XYkzrRqlfn5CHdrbYUVK2DOHNuRiEhWUlVPWU0DcdHy8qEzqQmxjB2czNp9zkwU/7m2mMN1TVx38mjboYRUVJRJEPeW19IirTLCysPvbOOpjwtshxGW5D99B4qKpDVGd/yzd05YfhodbV48T5xoOxJnuvVW+H//z3YU4nht3QrV1ZCfbzsSEckOVNUDuKb9gy15Oems3XfYkcscpwxL5cZTRzNn1EDboYTc8j0VnPGr//Le1lLboYh+0tqq2Vtex+hBA2yHEpYkUWxDaygultYY3Zk8GVavhiuvtB0JvPACvP667Sicy+OBtWuhvt52JOJ4+C/KyBJrYVNJtflHki2JYpe+d8543vruqY5c5njCiHTu/NwUR8YWbDNHppOdmsDTS/bYDkX0k5LqehqapTVGsEii2Mbhw1BXJzOK3YmKMsVjYh2wb/inPzUFW0THPB5TqXbNGtuRiOPh9UJaGkyYYDsSEclKqo4SHaUY5JI+gbaMGDiAIanOS6af8+5l16Ea22FYExMdxdXzclm6q5xtJdIqIxwU+FpjjJLWGEEhiWIbTU1wzTWmRYbo2tq18J3vmMTalupq2LJFZlm64qRlwqLvbr4ZnnrKXKQRwpbxQ1K4bNYIoqMibzaqt/7ySQF/X7nPdhifKiyv465XN/KP1cW2Q7HqijkjiY+JYtHSAtuhiH6wp9yXKMqMYlDIS442hgyBZ56BM86wHYnzFRbC735nlqDasmKFWS4siWLnhg0zM+TLltmORByPE06Aiy+2HYWIdF+aMZxfXHKC7TBc4fV1+3nOW2g7jE/95ZMCopTiqvzIaInRmYFJcVw0YzhvbjhAfZP0jnK7S2eN4N0fnM5QB87ghwNJFNtoapLm5D3lhJkq/9hz59qLwQ3efhueeMJ2FKKvdu2Cl16SHorCvqYWB/REcom8nHQ276+modl+MlLb0MyLK/dxwbRs2V8KfO+cCSz+n9NJiI22HYo4TvEx0YwbkvxpVVvRvyRRbOOBByAlxSSMomtZWZCbazdR3LzZVDtNT7cXgxtMmQLJybajEH31yitw2WV2l3kLobVmxn3/4aF/b7Udiivk5QyksaWVLQfs74V7ZU0xR+qbI64lRmey0xI+3WfrxMq0oucee38n72+TKrbBIoliG0VF5gW1E4q0uEF+vt1E8dlnYelSe+O7RWUl3HknfPKJ7UhEX3i9MHo0DB5sOxIRyY40NFPT0Ez6AHmC7IkZI80VzLWFlZYjgcO1jcwdlcHMkXJV1e9gdT2X/HEpb28qsR2K6KPWVs1vFu/gk13ltkMJW5IotiGtMXrH44HmZlNUxgalICPDzthuEh8PDz4Ib7xhOxLRF16v9E8U9h309VDMkr1APTI0LYHh6YmU1TTaDoVvnz2eFxbmR2RLjM4MSo6npKqep5YU2A5F9NGB6noam1ul4mkQSaLYRlGRtMboje98xyTXqamhH/vf/4arr4ZyuZDUrQEDYPp0qXzqRsXF5v+SFGwSth3wJYpD0xItR+IOSik+uO0Mbj1/otU4/O0wZA/XsaKjFNeelMvyPRVs2l9lOxzRB5+1xhhgOZLwJYliGzKj2DvRFveBv/OOKfBhI0l1I48Hli+HVqlF4SorV5r3kigK20qqTaKYLTOKPRYTbfdl1p6yWs5++AOeXbbXahxO9ZXZI0mMjeYZaZXhSnvKpDVGsEmiGEBr+OY34YILbEfiLj/+MVx7bejH9XpNv0vZT9oz+flmifC2bbYjEb3xxS/Czp3S21XYN3ZwEl87aRRDUuNth+Ia+yrq+MqfP2HJzjIr4//lkwJioxXnT8myMr7TpQ2I5eKZw3l17X4qau0vERa9U3qkgYTYKLl4FUQxtgNwEqXg/vttR+E+FRXwj3+YZuChmmFsbDT9G2++OTTjhQOPx8y+7t0Lkyfbjkb0lFIwdqztKISAWbkZzMqVTeG9kZEUx4qCCpbvqeDkcYNCOvaR+ib+vrKIz00fyhB5Id2pr58ymknZKSRKqwzX+cG5E/jm6WNlWXUQyYxigNpak/RIpeTe8XjgyBHYGsKK6evXQ329LMfrjUmTTPXT+fNtRyJ6qqUFbrgBPvrIdiRCQFlNgyN6ArpJUnwME7JSWLvvcMjHfnlVETUNzXxNWmJ0aezgZK6eN4rEOEkU3Uh+b8EliWKAV1+FzExZmtdb/mRt2bLQjVldDVOnSqLYG0pBlPzFu8qmTfDkk1BYaDsSIeDqJ5fzzb+uth2G6+TlpLOu6HDI+/W9unY/M0amk5cjLTG609TSynPevXy4/ZDtUEQPtbRqvvXcaumhGGTysjFAcbF5L1VPe2f8eNPwPpQVNc86CzZuhNzc0I0ZDv75T7PXTRq3u4P/b0ouiAgnOFhdT3aaLGHsrbycdA7XNVFQHtp/vM/fmM+jX84L6ZhuFa0Uj3+4m98u3mE7FNFDB6qO8saGA5T4qjGL4AhqoqiUekopVaqU2tjJcaWU+q1SaqdSar1SambAsWuVUjt8byEplVJUBGlpkJwcitHCR1QUfPWrMGpU6MaU5cF9ExUFa9bAqlW2IxE94fWaVQ6yRzE8KaXmK6W2+Z4Db+/geLxS6kXfca9SalTAsTt8t29TSp0f7Fjrm1qoqG1kqOx167XZowZy+oTB1DeFbtmu1prEuGipBtlDUVGKa+aNYuXeSjYUSasMNygoMxdepIdicAV7RnER0NWOqAuA8b63hcAfAQrNE/QAACAASURBVJRSGcA9gAeYC9yjlBoY1EgxiaK0xuib3/8efvSj0IxVWWlePD//fGjGCyf+mSnpp+gOXi/MnWuWDYvwopSKBh7DPA9OAa5QSk1pc9r1QKXWehzwKPCg72unAJcDUzHPsX/wfb+gKa1uACBLZhR7bdyQFJ75+lwmDw1NL6edpTWc88gHrLOwL9LNLps9ggFx0Ty9dI/tUEQP7Cn3t8aQHorBFNSqp1rrDwOvgHZgAfAXbRbuL1NKpSulhgJnAP/RWlcAKKX+g3kyDGpqUFQky06Px5Ej8NZbkBDwOiI1Fc44w3z84YdwuM3zVkYGnHKK+fi996Cm5tjjQ4aYtg5g+ibW15slp5WVkCXVvnttyBAz8/vGG/CVr0BODpSXw5Il7c+dMweGDoWDBztOLOfNg8GDzZLtjmYoTz0VBg40VVbXrWt//MwzISUFdu82v9O2zj0XEhNh+/aOCyXNnw9xcbB5s2kf0dbnP29mUNevh4KCY49FRZnjYKrnFhUdezwu7rOiP8uXQ0nJsccHDIBzzjEfL10KZW0q3/fH437WLPPxvHnt75sIC3OBnVrr3QBKqRcwz4mbA85ZAPzE9/FLwO+VUsp3+wta6wZgj1Jqp+/7fRKsYA9UHQVgqCSKfba6sJLymmNbMEwbnsrQtEQqahtZtbey3decmJPGkJQESo/Us25f+5muWbkDyUiKo6Sqng3F5vira4rZV3GUYemJwbkjYSo1IZZLZ43gOW8hP7pwMoOS41lTWElZm9/ZgLjoTyvYriyooLKu6ZjjKQkx5I/JBGDZ7nKO1Dcfc3zggFhmjzLVg5fsLKOu8diZ5kHJccwYaeZGPth+iMbmY5sfZ6cmMH1EGgDvbT1IS5veyMPTE5kyzFyU+M/mg+3uZ27mACZkpdDc0sr729rvyRwzOImxg5Opb2rhox3t27qMH5LMqEFJ1DY0s3RXebvjk7JTyMkYQNXRJpbvqWh3vL8e82sKK0mIjSIrRf4nBZPt9hjDgX0Bnxf5buvs9naUUgsxs5GMHDnyuIL57nfNC0DRezU1ZnncoTb/c/LyzFJHgFtvhRUrjj1+6qnmhTTAt77VPiG44AJ4803z8de//tk+0sREmD27f+9DpDjjDFi0CP77X7j6atiyBRYsaH/eK6/ARReZRKqj4//5j0mWliwxSWdby5aZGcx33zWVO9vatAmmTIHXX4fvfa/98cJCk8j+7W+mV2dbFRUmoXvmGXjoofbHm5pMQvinP8Ef/3jssYQEOGpe9/Loo/DXvx57fPBgKPXtj//5z02hq0BjxsCuXebju++GxYuPPX7CCZ8lx7fdZpLNQCefDB9/bD6+5RbzOwg0f7656LJhgyyzDmMdPc+13Y366Tla62alVBWQ6bt9WZuvbfcc2Z/Pj8MHJvKjCycxMSvluL5PpHpmaQH3vLap3e2//koeX5oxnO0Hj3DjX1a2O/6/18zm3CkJbCiq6vD4/93o4aSxg1heUMF3nl/z6e1fnj2CwSnS77K3rj1pFO9uPkh6omnQ/Lv3dvLe1mOLpYwZlMR7t54BwC/f3oa3TTI0fXgar3/bXAm8/43NbCyuPua4Z3QGL37DXAG869WNnzaN9zt70hCe/NocAG79+zoOHWk45vgXTxzGb6+YAcAt/7emXaJ5xdyR/Pzi6QAdPmZuPHU0d35uCvXNrR0e/+7Z4/n+uROoOtrU4fE7L5zMjaeNoaS6vsPjD1w0nSs9I9lbXtvh8d9cnseCvOFsK+n4Mf/ktbM5e3IC6/d1/Jh//sZ85o3NZMbIgew+VCutMYJMBbsKl29G8V9a62kdHHsD+LnW+mPf54uB/wecBcRrre/33f5joE5r/XBXY82ePVuvXNn+QSVCo7Cw/cxKYuJnPfu2bm1fRCU5GSZMMB9v3mxmDAOlpsK4cebjDRvMi38wMy4y+9s3R4+axCQ31yzhrakxs3ZtjRljihRVVX2WFAUaN878fiorYU8HK3UmToSkJPOY6Khq5+TJ5vFRWtp+Rg9g2jSTCB44YN7aOuEEiIkxFw8Otr9oyowZZslmR49LpcxxMLONFW0uesbEmO8P5r5XtbmoGRdn4gPYscPMpgfq7nGflGR+PtD94150TCm1Smvt2stFSqnLgPO11jf4Pr8amKu1/nbAOZt85xT5Pt+FmTm8D/hEa/1X3+1PAm9qrV/ubDx5frSrqaWV7QePtLvwM2JgIukD4qhpaKagTcIAkJMxgLTEWKrrmyjsoBjOqEFJJMfHcLiukaLKo5/ePm5IMgnSF7BPDlQdZWiamY0tKKulpuHYGcG4mCgm+C6Y7D5U0y5RS4iNZtwQU+xiZ+kR6puOnfIbEBfNmMHm+PaDR9rNGKYkxJDr23e35UA1La3HPmjSEmPJyTCzGpv2V7V7TA1MimO4bzZ5Y3H7GbnM5DiGpiXS0qrZcqC63fEhKfEMSU2gsdk8ZtvKSk1gcEo89U0t7CytaXd8WHoiGUlx1DU2s/tQ+8d0d4/5kZkDSE2IpepoE/squn7MKxRpA2LbnSP67znSdqL4Z+C/WuvnfZ9vwyw7PQM4Q2v9jY7O64w8EQohRGQIg0RxHvATrfX5vs/vANBa/zzgnLd953yilIoBSoDBwO2B5wae19l48vwohBCRo7+eI223x3gNuMZX/TQfqNJaHwDeBs5TSg30FbE5z3ebEEIIEQ5WAOOVUqOVUnGY4jSvtTnnNcBf9ftS4D3fnv7XgMt9VVFHYwrCtVngLIQQQhyfoO5RVEo9j5kdHKSUKsJUMo0F0Fr/CXgTuBDYCdQB1/mOVSilfop5IgW4z1/YRgghhHA7357DWzAXQaOBp7TWm5RS9wErtdavAU8Cz/qK1VRgkkl85/0NU/imGfiW1jp0vReEEEJEhKAvPQ0lWVojhBCRwe1LT0NNnh+FECJyhMvSUyGEEEIIIYQQDiOJohBCCCGEEEKIY0iiKIQQQgghhBDiGJIoCiGEEEIIIYQ4hiSKQgghhBBCCCGOIYmiEEIIIYQQQohjSKIohBBCCCGEEOIYYdVHUSl1CNh7nN9mEFDWD+E4ZZxwHUvuk4xla5xwHctt9ylXaz24P4KJBC57fgzXseQ+yVi2xgnlWOF4n0I5Vn+N0y/PkWGVKPYHpdTKUDRxDtU44TqW3CcZy9Y44TpWON4n0b/C9TEif2POHydcx5L7JGPZGqenZOmpEEIIIYQQQohjSKIohBBCCCGEEOIYkii293iYjROuY8l9krFsjROuY4XjfRL9K1wfI/I35vxxwnUsuU8ylq1xekT2KAohhBBCCCGEOIbMKAohhBBCCCGEOJbW2tFvQA7wPrAF2AR813d7BvAfYIfv/UDf7Qr4LbATWA/MDPheD/m+xxbfOaqTcQ4Ch4BtwKUB47wP/BPY6jvvb23HARKA/cBRoB54KWCM0YAX2OMbYz/Q4Bvr2g7u01vAxo7uk2+c5UCpb5xS4CudjLMFKPKNswO4OWCc9b6fySbgCeATX0y3tvk9rPSN0wAsA6Lb/B72ABVALdACbGxzvNp3bDPwFDCto7GAJ33fpxmoApJ9t58GrPbd/g3f76Iw4Od3e5uxjgIbgLXAlzoZ6wWgxne/qoDbOhhro+/nt9f3s9wJ3Bvw8yv2nbMeeNv3c287Tg5Q7hunHlgS8PO7zPezb/X9jDu7T0W++7UB+Bg4r5P79A5Q5xunArivg3E+5/v5dfb4q/B9fY3vaycdx1grfT+/I75z/8Wxj/OtwG5AA/kdjeP7nkd8v9OjvrH8j4t44EWgwPfzCbxPbR8TPXn8PeeLqwo47It9HpAGvO77+lrfOJ09JvzH1vq+fl0n9+lZ3xj1vvjO6uTxd9j38YE2f1O7MI+rXb7P53Zyn14K+Nkd9o31PXr3N1Xl+x1s8n2/mZ2M9WHAWGUBYwU+Jmb7zp2P+R+7E7g94Huc7YtrLeaxPq6T54Z/+362m4A/0fHf1Gzbz2Hh8PzYZqxS3+/9IHB+m8fjQWA7n/3d9OV5awfwGvBf5Dmyr8+R3T1vdfs/yvf73s9nz1truxjreP9v/BfzXNzgu2/f6+J5KxTPkf7nrc4eE7t9x2ro/PkxAfP/1v9acCWdP+/X0PFjotQXq8a0TOhsrCeBRj77H7+6k+fHnf+/vXOPt6os8/j3CeQSiiIiongJRVFHwULNLl5HKT4qOJQTjjZT2W2y5kNWTtNMTU1p081p0pxSUjKdSSXSGsuazOyGWQqoYF4y5cTNCyjKxQ4888fvWey1N2vtc4DD6WjP9/Phc9h7r72e9b7r9z6/933Xu9amXhNL4++9wGyk4SqdXxfndH3Eek283+qRT9acp+72z2bGNoVn3Y9ySpVv9YZH9kRf8KBS+dfGOZtR5Vv0IX98IVxR7ATOd/eDUUfyPWZ2CBLej9x9LPCjeA3wemBs/HsHcBmAmb0KeDVwOErARwLHtcYBpqHGuQo4D7gcuDXiDAUGuPs44AJgWGscdBLvB3YCRgKvM7MT47N/By4GXoUa4Q7x/aeBTwIfK5VpGbBvmzKtj/3NB3ZB4v1XMxvaEuenyNz+GHHOAS4EfhH1uU/EPDSO+Wrgc+UTYGb9UMM7JLYZhxoRxXmIWN9AiWI6sF/5PAFvAv4tPh8cZXpfayxgBkocR8UxnxfvPwb8HXAtSqgfjM8nAivjs89GrG+hRHezu0+IslbF+hfgWHcfBHwd+FAccxFrDjAL6WUDStjTgHcD98R5+irwv+5+ODKPOyvidAJTI84IpMGi/u4F/grp4YttyrQGafHmqIO31pTpDcDuqI5vA6ab2StLcW6P4/k4Mq/N9AdMBj4PDIh9PrWVseYCF0fbnR5l2pHmtvsDlFQfRW2uKk5xDHu7+2DgKhq6eFvs9xjgItRGq+qvu/q7BunlfNQJvRSZw3uQAZ4EnIY6AXWaWArcHdo7Dji3pkz9kIkMQh3DY+P9Vv2dDhwP7NrSpmajjvAN8fqcmjK91d0HR91diTrVc9iyNrU38Ck00H8MOKMm1qkR56XAT5AZzaFZf0VOuRSdh0OQdg6JfVwG/E3U37XAP1fUHcCZ7j4etc8RyABpjfUip7f8sYh1CdL3nqgzeDnw4Yjxs/g3BxgPjK6I1aVvxTGvQp2hyhyVHtnWI7vjW93JUZ1oYF341r7AJypiXc225423o/w3CJ2PC6JuWn2rXY7qKY+ci7Txaio0EfX3PeDbsb86f1wPHBz5cCdgDGorVMSaQrUmJgFfQoOLdrFmoEH93shLrov3y/54IWpTdZr4Puo7HYY84raKOCCdz0Dn6hakQ2j2yCmozR3D1vfPZsTxfgC1z6uRF7f61vlsf4/skb6gu/8WGB1xdkT++Mf4uKz1l9CH/LHPDxTdfam73xX/X42EshcS4qzYbBZKnMT7X3cxF9jFzEahGZlBqPM7EA3SllfEmYIqf2F8NAC4J8xlBGrsoNmtr1XEOQQNLDuRANYBrzQzA05EVxiXAr8B1rn7Y2h0Px+dyFlmtiNwIEpklWUC9ohj+Qk6j/3QrMbrWuJ8Hngz6pDfhxIWyGTHoNmPSfHed5GoCuEWHAU86O7FlZ+lwCtKxzYrYl0EHIEG2s+Wz5O731w6T78CdnH3O1tjufsz7n47SogW8XD337v7AtSwVqHz95C734M08XOULApN3BaxcPcVNbEedPe74tz0j+PeqxTrOTQLfBSNmeXd47jWxW6+CkyNfQAsroiz1N1/Gi/XxX6HxWeLInk8H8dQVyZHiW4qmrn7XZv6ezb2NQjpwktxQDNso4AfVukvNHZJ7KNd/XUV63k0I4a7fzfqchDNbfcipFeAJ6riFOEAop4HF69p1t9PUXstZv421V939Yc6usei2cxfAaPcfVXE2wm1m0eQUdRp4iHU0a6tu8gnxwAzo0wD0QwjrfqL9tCBOh7l3DcFGeLUeH1K3Xkq1d0BwJPu/uiWtKnYR1F/g9HV5tpYSBN7AcsjVll/oDb1kLv/zt2fR1f3pxS7QQN+kNaXUEFLrAE0ckVrrBctveWPRSzkS//j7k+i2f4VwJmoQ3YsGrRMjXP6l62x6IZvRbjLUIezMkelR7b1yO74Vpc5qsW3nkU5YqeKWP3Y9rzxYOi4PzpXHciLW32rne/3lEcWvjWJak2AJi1O7qL+PM45UfaXsHmOeh74rbv/iGpN3A38B5p4a+vFpZd1/vg5dJW1ThP/hNquIy/d0BonfGt/YGZsNxcYXhwGDY8civyquGK9xf2zoPDiwUCnu69q9S13v6sXPLJH+oLlWOhcrEFXXFt961D6kD/2+YFiGTPbDyXZO4CRRSOMv7vHZnuhE1RQJJxfokvUS+PfLe6+qCLMXqjDVsQpkskY1AD2M7O70Uj/8dY4yMxeb2bzUcPvj8Q7HIm6M7bfARhQKtM8tDxoKZpV/DSauaktEzLqf4w4P0MGNq4lTkfUzepSmQYCQ5BZjAH2MLP+qDHtXVMni83sloi1Mv5B9XnYAwm47jydg2avKjGzK9FszEA0m1ZFcUz7RbnmAkNLifmDwP5mdrGZDewi1jJgAmp8d9TEWkmj/l4a2xZl2i/2Ma7N8RL19wRKplUzdSPalOlcNKM2FtXfp7uIsxYZ2Q3uXlemxTX6K8plFd/bmlhF2y2uFNS13XY4Mu/ngRNo1HO5beyBkvYEKjTRTf2NQe36KjQTfriZDUED54NRUr4HXYGu1ETUxx5mtqCN/oo4D0SZpiBDrGM0ykPlNjXS3ecDu3dVjyWdT0RXrqvoqk1diM5hd3S+Aun5knaxSq+LnAbS+s1m1kH3tL4C5bcb6rb7c6AX/bGskYVoSdwQpOeLUN69Al2J21bfqstR6ZHd88htyVHlWCvQ5GLV1Ytd6dm8sRGtxuqOb21vj6zSRLd9y8z6mdkz6KrkknbHRHtNdKevPhy13bPRwKYow+LYTyeNieq6vszuZrYD9forfOvK6Ad/BA36oNkjr0GDzX3Y+v7ZGHTVbU2UaVx4cR295ZE91Rf8NloSW+VbI+hD/viCGSjGDOJstHb9mXabVrznZnYAEvFoVOEnmtmxFdsOAP6hJY6jAd/LgfXufgSabTm7NY67/wAtfXCUyNchI209ruL1bLREZX2UcwJaczynqzK5+/eRMT8Sx7IQLc9oxdCyhqYyuftKdOl8CGrUv2/zfdx9EjKLHWiItoqPA/fVnKeXAreXZiqrCvYW4GhUJ39ds1lxFbCov3Wlzz6MGupqZGIXdBFrLJol+3bNMQ9Gs+OtmihYg5ZiLWpzvKClCg+j2agjt7BMM9CS0KfR0ogvtCnTJJRgvwecYmZ/URNrAC3621K6E6vUdi+hWl/d4dXuPhx10nZDy4ahuW0U/7+SzeuvoCv9Fe18ZzRD+DvU0ZyEOqp7ooHouaiTUaWJD6OlQkdSr78iztnI3J5AS4Y2I+rvMmBZF7mvltD5vuhKy8aazdrpr9jH03Sh89DEPijXLqvZrDKnxd8ZwGR3H033tD4KdeJOrNvuxU4v+mNx9bvQSDFjXuj5MpR3n0Mz85vF2gLfgooclR7ZbY9s51vdyVEF70VL8H6MPKiVnswbB6CrSF+rqZve9MiBVGiibp81cTa4+1A0CNwNLYfdjGi/7TTRHQ5CXnIDuo3mWKr7ncfRvkxfpl5/5Xb+azSYKfJE2SM/hJZaz2Hr+2f90cqrE9EEwGgaS+ibC9V7HtlTfcHTUPmXU+1bfcofXxADxZjhmA1c4+7fireXx5IZ4u+KeL+D5hm/0WiG4wxgrrs/61p28D20JPQMM5sX/45G65wXluJ0omTcQWO2FdTZH29me5vZPLSe/SQAd/+Uu09w9xNozKyPQVcj55nZ6bHfoaUyjUYzFZOAV5jZYmQYB6LZi/HFcaLL0ktKsQ5DMyB7ooa6W2nbs2I/j5bKtB4JGtTYH3b3Y9AVmweRSGfEPj5RrlN3X4fMcmTU1yAzu9fMTjezvZGx/x+NDmL5PH0WXT15f+n8nB2xrqCZjSjhT4vvFvV8OuqgLwVObam/Z8xsVMzs7BF1fyWNNfSbxQptXY/W9L+sItYktPb+iVL9rUGNfJP23H0Duml8WkX9lTX8DXRj8ZQiTsTaEy2tqSrToeien8eiTN8EXmW6L+ZdEau4d4TSeZqNzvXrzOzoiDMRJfalwFtaYq1saVObEuA2xDo+PitmGKG+7ZZ5e9TNFRGj0PsydA/PlNDb3sCtZvau2M+OaAlakyYiVnf010Gc29iueADDu+Pc3I2WjAwEVldpIljh7utp1l+5TB1Ah7vfEdr5KnB0iyYOQsuiZqPZx8KYivpbbmbjgRUt9VjXpiahZbknR310u03F9kWMbwLT2mkCmdIDxH1upVgT0f0RlXnazEYA40sz/Ju0XsrTVfq7icbSnD8retEfJ8a2F9CskSdQu+qgkaNuQF6wtb71ptjPZjmK9MiCdh7Z1reCrnJUk7bQlYtpFTlqJT2QNyLWtUh7u7WUqcgbdTmqpz3yeLSkulITNb61me+XYi1HV7T/togTsYbTyPF1mhjF5gOXzTTh7kvCS65CA7OjUNu8NeKdhwZmj7fpy2xA/dWy/jbzLbR8ewS6qPLy0PVMdG7eiXxyIHDbNvTPCo/8JTqfQ4pYZd8qaXR7e2SP9AWD16P7L6+nui+4gj7kj31+oGhmhgS4yN3LI+eb0FPQiL83lt5/s4lXAk+HMB8DjjOz/iGs42Kfc1w3hR6BRDAXGG1mA83sZWjG9LDooHbSuAH0WXTVoQMlogXu/hkzGxnfw8yORFeqbooTOwcl2+/QuBp5pZkNQ53P2ehJc3uiG1lnos7W21EDPCJiPQZ0mtmuZjbczAYjIQ9Ha+p/GHGOQDNY84BRZjYsYoEaKuhJXjfG+3+Pbhp29FCBCe7+UTQLO87MXhaxTkY399+BLq8XN+jfiGZSrm89T2Z2Lkq8l7t7Oel9I2KdG+esPAs9FD0YCHdfHOfppijfO9Gs7RwzG4A6Ft+JWKNoaGIqavh1sWbGMa+riTUWLTEYEOUv1noPCm2+P+rP0CzR/a31Z5rtupbG0wQnA/cXcSLWEmSEVWWagrR2fpTpZKTdDWjQeXERx8wONbNdTMukTgtN3B8Dkgmo03M70tNQNtdfuU1tmjnfhlgn0P22W+byqJtzzWxIJHtMS09OQZM5i9Hs5K3AV9B9I501muhSf/H6VGTcH43tTkL6fwB1lo5AnYh+cTxNmoh9nEdDE2X9bSoT8WRlMzsotjsLdUrKmvgtGqAuonlZalF/N6F2fmNLPda1qemo47A1beqAUozT0Hmu0sSoiHUWMtHWWL9GDzO4Exhbqr83xXGsBHY2swNjP5u0XtRLa6zQ3+Qi1p8TveWPce5+gzp1w4BLw+fGonw/GV1dKHLUSehcb7FvRaz9kfdW5aj0yAZ1HlnrW/G9LnNUfHZdHO/FNNp9a446mZ7JGzOjLP0qylTkjboc1dMeeQJ6yEqdJqp8q9X39zOzg2DTFa/Xogef3FGqvyeBj1KjiVKsNTTTqonDzGynOGdnoEHVvXH+bkU6PxNdWa/TxCVoMDy9RX+bNBH94OJWieloQrDw4muRR34FDSD7A1dvbf8MTfoujjo8LbZZWOFbRR9ue3tkj/QFo/zT0SCvri+4kL7kj94HHvHd7h/wmqjsBSiZz4tCD0c3Lj8Yf3f1xuO/L0VL/O6h8Sj2fkjAi+IkfKFNnKU0riKeWYpzB5opWYBmL66oiDORxuOQ1wBfLsUYg25S74hYxc2369Hl49Yyjafx6O+mMqGn082j8ejqxcCEmjj30Hik9BJkEkWcZUhAC1ESLh4xvSr+PxTdL/BAfP959Hjh/hGrOObFEes51FnfiBrcG+Jzj/ooHon8mYpYO6ObnlehTsJG9Mjht6ElMh2x/6djf4/QeBz5rNKxrEED+UUoIYypibUg9lM8JnsB0lYRa23p84fj71I0ICnqb1XUXfFI6T9U1N9psZ/ikciPo6dDgpJ6R9RrUUdVZVoSZboX3RNwVEWZ9o/PC/09CfxrS5z1UVaPc1alv6fi+xvjO5/bylhFmVbHsRdX55egdvQg6mj8IT5bFue3tf72j/eLWPPQ/Q4gk7uehtYX19Rfd/Q3NI5jcWy7FmloGJrl+wHSgaP2VKeJp2ho4gaqNfGSOI7ifC8G9okyteqveKiAozb1voj1cMR6OF6PqyhT0abujbJdV6q7LWlTa2m0qWvQErEqTdwZddyJ8m3/Cv0tR0/Lm4zyysPAR0p58ozYx3yk9TEVvjAyYi1AD5v4UrtYf2ofe6H7Y0usZVG369AS8CLWo6GH+5A/DmuNRfd86yHUuW2Xo9Ij6z2yO77VnRz1Wpp96ylgWk2Oep5tyxuLSsf8OA0dV/lWXY7qKY8s+1adJh6NOtsYnz1TUX/H0+xbc9k8RxWxOqnWRPHTLp007v2r0sSvaf55h+InP1r98X7qNbEx6nZe1NHTrWWKfRb3Oq6NbS6M91s9sjj2re2f/TyOay0aIH0X5ZQq3yraw/byyJ7qC45EE26dUf52vvUb+og/WnwxSZIkSZIkSZIkSYAXwNLTJEmSJEmSJEmSpHfJgWKSJEmSJEmSJEnSRA4UkyRJkiRJkiRJkiZyoJgkSZIkSZIkSZI0kQPFJEmSJEmSJEmSpIkcKCZJH8TMNph+PPU+M5tvZu83s7btNX636azeOsYkSZIk6W3SH5Ok98iBYpL0Tda6fjz1UPSjqpOBj3Xxnf3QD50nSZIkyYuV9Mck6SXydxSTpA9iZs+6+46l12PQD6juBuwLXA0MiY/Pc/dfmNlc4GD0o7mzgP8EPo1++HcgcKm7f6XXCpEkSZIkPUz6Y5L0HjlQTJI+SKsRxnsrgXHAamCju68zs7HAf7v7RDM7HviAu58a278D2N3dP2lmA4GfA29090d6tTBJkiRJ0kOkPyZJ79H/T30A0CaaHAAAAVFJREFUSZJ0G4u/OwCXmNkEYANwYM32pwCHm9kb4vXOwFg0o5okSZIkLxbSH5NkO5ADxSR5ARBLazYAK9C9GMuB8eg+43V1XwPe6+639MpBJkmSJEkvk/6YJNuPfJhNkvRxzGwE8F/AJa614jsDS919I3AO0C82XQ3sVPrqLcC7zWyH2M+BZjaEJEmSJHkRkP6YJNuXvKKYJH2TwWY2Dy2j6UQ3538hPvsyMNvM3gj8GHgu3l8AdJrZfOAq4IvoSW93mZkBjwNTe6sASZIkSbIdSH9Mkl4iH2aTJEmSJEmSJEmSNJFLT5MkSZIkSZIkSZImcqCYJEmSJEmSJEmSNJEDxSRJkiRJkiRJkqSJHCgmSZIkSZIkSZIkTeRAMUmSJEmSJEmSJGkiB4pJkiRJkiRJkiRJEzlQTJIkSZIkSZIkSZrIgWKSJEmSJEmSJEnSxP8D7BY2w6ZkTFYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot score vs time for each threshold\n",
    "thresholds = class_res_df['threshold'].unique()\n",
    "\n",
    "i = 1\n",
    "for thresh in thresholds:\n",
    "    class_series = class_res_df[(class_res_df.threshold == thresh)]\n",
    "\n",
    "    fig = plt.figure(i)\n",
    "    plt.subplots_adjust(wspace=0.5)\n",
    "    plt.subplots(figsize=(15,5))\n",
    "    \n",
    "    plt.subplot(121)\n",
    "    plt.title('Alg: Graph Color, Data: %s, Thresh: = %.2f' % (dataset, thresh))\n",
    "    plt.ylabel('Num Colors')\n",
    "    plt.xlabel('Date')\n",
    "    \n",
    "    plt.plot(class_series['date'], class_series['num_colors'], 'b--', label='Class Alg')\n",
    "    plt.legend(loc=0, prop={'size': 13})\n",
    "#     plt.xticks(ticks=class_series['date'][::3], labels=[x[0:7] for x in class_series['date']])\n",
    "    \n",
    "    plt.subplot(122)\n",
    "    plt.title('Graph Density vs Time, %s, thresh=%.2f' % (dataset, thresh))\n",
    "    plt.plot(class_series['date'], class_series['density'], '--')\n",
    "    #plt.xticks(ticks=class_series['date'][::3], labels=[x[0:7] for x in class_series['date']])\n",
    "    plt.ylabel(\"Density\")\n",
    "    plt.xlabel(\"Date\")\n",
    "    \n",
    "    i += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'Date')"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 2160x360 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot score vs time for each threshold\n",
    "thresholds = quant_res_df['threshold'].unique()\n",
    "low_thresh = thresholds[1]\n",
    "high_thresh = thresholds[3]\n",
    "\n",
    "quant_series = quant_res_df[(quant_res_df.threshold == low_thresh) & \n",
    "                            (quant_res_df.valid_coloring == True)]\n",
    "class_series = class_res_df[(class_res_df.threshold == low_thresh) & \n",
    "                            (class_res_df.valid_coloring == True)]\n",
    "class_series = class_series[class_series['date'].isin(quant_series['date'])]\n",
    "\n",
    "assert quant_series.shape == class_series.shape\n",
    "\n",
    "fig = plt.figure(1)\n",
    "plt.subplots(figsize=(30,5))\n",
    "\n",
    "plt.subplot(141)\n",
    "plt.title('Alg: Graph Color, Data: %s, Thresh: %.2f' % (dataset, low_thresh))\n",
    "plt.ylabel('Num Colors')\n",
    "plt.xlabel('Date')\n",
    "\n",
    "plt.plot(quant_series[\"date\"], quant_series['num_colors'], 'r--', label='Quant Alg')\n",
    "plt.plot(quant_series[\"date\"], class_series['num_colors'], 'b--', label='Class Alg')\n",
    "plt.legend(loc=0, prop={'size': 13})\n",
    "plt.xticks(ticks=quant_series['date'][::4], \n",
    "          labels=[x[0:7] for x in quant_series['date']])\n",
    "\n",
    "plt.subplot(142)\n",
    "plt.title('Graph Density vs Time, %s, Thresh: %.2f' % (dataset, low_thresh))\n",
    "plt.plot(quant_series['date'], quant_series['density'], '--')\n",
    "plt.xticks(ticks=quant_series['date'][::4], \n",
    "          labels=[x[0:7] for x in quant_series['date']])\n",
    "plt.ylabel(\"Density\")\n",
    "plt.xlabel(\"Date\")\n",
    "\n",
    "\n",
    "quant_series = quant_res_df[(quant_res_df.threshold == high_thresh) & \n",
    "                            (quant_res_df.valid_coloring == True)]\n",
    "class_series = class_res_df[(class_res_df.threshold == high_thresh) & \n",
    "                            (class_res_df.valid_coloring == True)]\n",
    "class_series = class_series[class_series['date'].isin(quant_series['date'])]\n",
    "\n",
    "assert quant_series.shape == class_series.shape\n",
    "\n",
    "plt.subplot(143)\n",
    "plt.title('Alg: Graph Color, Data: %s, Thresh: %.2f' % (dataset, high_thresh))\n",
    "plt.ylabel('Num Colors')\n",
    "plt.xlabel('Date')\n",
    "\n",
    "plt.plot(quant_series[\"date\"], quant_series['num_colors'], 'r--', label='Quant Alg')\n",
    "plt.plot(quant_series[\"date\"], class_series['num_colors'], 'b--', label='Class Alg')\n",
    "plt.legend(loc=0, prop={'size': 13})\n",
    "plt.xticks(ticks=quant_series['date'][::4], \n",
    "          labels=[x[0:7] for x in quant_series['date']])\n",
    "\n",
    "plt.subplot(144)\n",
    "plt.title('Graph Density vs Time, %s, Thresh: %.2f' % (dataset, high_thresh))\n",
    "plt.plot(quant_series['date'], quant_series['density'], '--')\n",
    "plt.xticks(ticks=quant_series['date'][::4], \n",
    "          labels=[x[0:7] for x in quant_series['date']])\n",
    "plt.ylabel(\"Density\")\n",
    "plt.xlabel(\"Date\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "ename": "ConversionError",
     "evalue": "Failed to convert value(s) to axis units: array(['2016-10-31', '2016-10-31', '2011-05-31', '2013-11-30',\n       '2015-02-28', '2016-05-31', '2016-10-31', '2017-08-31',\n       '2008-06-30', '2009-04-30', '2009-09-30', '2010-12-31',\n       '2011-05-31', '2012-03-31', '2012-08-31', '2013-01-31',\n       '2013-11-30', '2015-02-28', '2016-05-31', '2016-10-31',\n       '2017-03-31', '2017-08-31'], dtype=object)",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\matplotlib\\axis.py\u001b[0m in \u001b[0;36mconvert_units\u001b[1;34m(self, x)\u001b[0m\n\u001b[0;32m   1549\u001b[0m         \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1550\u001b[1;33m             \u001b[0mret\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconverter\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconvert\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0munits\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1551\u001b[0m         \u001b[1;32mexcept\u001b[0m \u001b[0mException\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\matplotlib\\category.py\u001b[0m in \u001b[0;36mconvert\u001b[1;34m(value, unit, axis)\u001b[0m\n\u001b[0;32m     51\u001b[0m             raise ValueError(\n\u001b[1;32m---> 52\u001b[1;33m                 \u001b[1;34m'Missing category information for StrCategoryConverter; '\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     53\u001b[0m                 \u001b[1;34m'this might be caused by unintendedly mixing categorical and '\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mValueError\u001b[0m: Missing category information for StrCategoryConverter; this might be caused by unintendedly mixing categorical and numeric data",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[1;31mConversionError\u001b[0m                           Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-56-11f1c4bcd886>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0mfig\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfigsize\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m15\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m10\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mquant_res_df\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'r--'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlabel\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'Quant Alg'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      3\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mclass_res_df\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'b--'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlabel\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'Class. Alg'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtitle\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Min Colors vs Density\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mylabel\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Num Colors\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\matplotlib\\pyplot.py\u001b[0m in \u001b[0;36mplot\u001b[1;34m(scalex, scaley, data, *args, **kwargs)\u001b[0m\n\u001b[0;32m   2793\u001b[0m     return gca().plot(\n\u001b[0;32m   2794\u001b[0m         *args, scalex=scalex, scaley=scaley, **({\"data\": data} if data\n\u001b[1;32m-> 2795\u001b[1;33m         is not None else {}), **kwargs)\n\u001b[0m\u001b[0;32m   2796\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2797\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\matplotlib\\axes\\_axes.py\u001b[0m in \u001b[0;36mplot\u001b[1;34m(self, scalex, scaley, data, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1666\u001b[0m         \u001b[0mlines\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_get_lines\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1667\u001b[0m         \u001b[1;32mfor\u001b[0m \u001b[0mline\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mlines\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1668\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0madd_line\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mline\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1669\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mautoscale_view\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mscalex\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mscalex\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mscaley\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mscaley\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1670\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mlines\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\matplotlib\\axes\\_base.py\u001b[0m in \u001b[0;36madd_line\u001b[1;34m(self, line)\u001b[0m\n\u001b[0;32m   1900\u001b[0m             \u001b[0mline\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_clip_path\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpatch\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1901\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1902\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_update_line_limits\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mline\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1903\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mline\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_label\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1904\u001b[0m             \u001b[0mline\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_label\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'_line%d'\u001b[0m \u001b[1;33m%\u001b[0m \u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlines\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\matplotlib\\axes\\_base.py\u001b[0m in \u001b[0;36m_update_line_limits\u001b[1;34m(self, line)\u001b[0m\n\u001b[0;32m   1922\u001b[0m         \u001b[0mFigures\u001b[0m \u001b[0mout\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mdata\u001b[0m \u001b[0mlimit\u001b[0m \u001b[0mof\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mgiven\u001b[0m \u001b[0mline\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mupdating\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdataLim\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1923\u001b[0m         \"\"\"\n\u001b[1;32m-> 1924\u001b[1;33m         \u001b[0mpath\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mline\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_path\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1925\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mpath\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvertices\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msize\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1926\u001b[0m             \u001b[1;32mreturn\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\matplotlib\\lines.py\u001b[0m in \u001b[0;36mget_path\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m   1025\u001b[0m         \"\"\"\n\u001b[0;32m   1026\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_invalidy\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_invalidx\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1027\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrecache\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1028\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_path\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1029\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\matplotlib\\lines.py\u001b[0m in \u001b[0;36mrecache\u001b[1;34m(self, always)\u001b[0m\n\u001b[0;32m    672\u001b[0m             \u001b[0mx\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_x\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    673\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0malways\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_invalidy\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 674\u001b[1;33m             \u001b[0myconv\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconvert_yunits\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_yorig\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    675\u001b[0m             \u001b[0my\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m_to_unmasked_float_array\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0myconv\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mravel\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    676\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\matplotlib\\artist.py\u001b[0m in \u001b[0;36mconvert_yunits\u001b[1;34m(self, y)\u001b[0m\n\u001b[0;32m    190\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0max\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0max\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0myaxis\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    191\u001b[0m             \u001b[1;32mreturn\u001b[0m \u001b[0my\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 192\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0max\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0myaxis\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconvert_units\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    193\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    194\u001b[0m     \u001b[1;33m@\u001b[0m\u001b[0mproperty\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\matplotlib\\axis.py\u001b[0m in \u001b[0;36mconvert_units\u001b[1;34m(self, x)\u001b[0m\n\u001b[0;32m   1551\u001b[0m         \u001b[1;32mexcept\u001b[0m \u001b[0mException\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1552\u001b[0m             raise munits.ConversionError('Failed to convert value(s) to axis '\n\u001b[1;32m-> 1553\u001b[1;33m                                          f'units: {x!r}') from e\n\u001b[0m\u001b[0;32m   1554\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mret\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1555\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mConversionError\u001b[0m: Failed to convert value(s) to axis units: array(['2016-10-31', '2016-10-31', '2011-05-31', '2013-11-30',\n       '2015-02-28', '2016-05-31', '2016-10-31', '2017-08-31',\n       '2008-06-30', '2009-04-30', '2009-09-30', '2010-12-31',\n       '2011-05-31', '2012-03-31', '2012-08-31', '2013-01-31',\n       '2013-11-30', '2015-02-28', '2016-05-31', '2016-10-31',\n       '2017-03-31', '2017-08-31'], dtype=object)"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(1, figsize=(15,10))\n",
    "plt.plot(quant_res_df, 'r--', label='Quant Alg')\n",
    "plt.plot(class_res_df, 'b--', label='Class. Alg')\n",
    "plt.title(\"Min Colors vs Density\")\n",
    "plt.ylabel(\"Num Colors\")\n",
    "plt.xlabel(\"Density\")\n",
    "plt.legend(loc=0)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
